{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating Container for Simulated Data\n",
    "In this notebook, I want to derive a HDF5 container for a given simulated network (simulated by `NetSim`). For that, I have to create simulated feature vectors and a training and test split.\n",
    "The results should then be put in a HDF5 container."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import h5py, os, sys\n",
    "np.set_printoptions(precision=1, suppress=True)\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "sys.path.append(os.path.abspath('../GCN'))\n",
    "import gcnPreprocessing\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# params\n",
    "test_ratio = .3\n",
    "pos_distr = (50, 60) # mean and variance\n",
    "neg_distr = (45, 60) # mean and variance\n",
    "num_features = 24\n",
    "NETWORK_TYPE = 'clique'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Network and Insert Positions from Disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1053 2275\n"
     ]
    }
   ],
   "source": [
    "if NETWORK_TYPE == 'random':\n",
    "    if not os.path.exists('../data/simulation/random_network/network.edgelist'):\n",
    "        for i in range(1, 1000):\n",
    "            G = nx.barabasi_albert_graph(n=1000, m=i)\n",
    "            if nx.number_of_edges(G) > 1500:\n",
    "                break\n",
    "        nx.write_edgelist(G, '../data/simulation/random_network/network.edgelist')\n",
    "        x = list(np.random.choice(list(nx.nodes(G)), size=190).reshape(-1, 5))\n",
    "        insert_positions = [list(i) for i in x]\n",
    "        network = G\n",
    "        with open('../data/simulation/random_network/insert_positions.txt', 'w') as f:\n",
    "                count = 1\n",
    "                f.write('# subnetwork insert positions. Each row corresponds to a subnetwork and each column to a position in it.\\n')\n",
    "                for m in insert_positions:\n",
    "                    f.write('Subnetwork {}: '.format(count))\n",
    "                    for i in m:\n",
    "                        f.write('{}\\t'.format(i))\n",
    "                    f.write('\\n')\n",
    "                    count += 1\n",
    "    else:\n",
    "        network = nx.read_edgelist('../data/simulation/random_network/network.edgelist')\n",
    "        insert_positions = []\n",
    "        with open('../data/simulation/random_network/insert_positions.txt', 'r') as f:\n",
    "            for line in f.readlines():\n",
    "                if line.startswith('#'): # comment\n",
    "                    pass\n",
    "                elif line.startswith('Subnetwork'):\n",
    "                    positions = line.split(':')[1].strip().split('\\t')\n",
    "                    insert_positions.append([int(i) for i in positions])\n",
    "\n",
    "elif NETWORK_TYPE == 'star':\n",
    "    # read the network and insert positions\n",
    "    network = nx.read_edgelist('../data/simulation/star_network/network.edgelist')\n",
    "    insert_positions = []\n",
    "    with open('../data/simulation/star_network/insert_positions.txt', 'r') as f:\n",
    "        for line in f.readlines():\n",
    "            if line.startswith('#'): # comment\n",
    "                pass\n",
    "            elif line.startswith('Subnetwork'):\n",
    "                positions = line.split(':')[1].strip().split('\\t')\n",
    "                insert_positions.append([int(i) for i in positions])\n",
    "    print (network.number_of_nodes(), network.number_of_edges())\n",
    "\n",
    "elif NETWORK_TYPE == 'clique':\n",
    "    # read the network and insert positions\n",
    "    network = nx.read_edgelist('../data/simulation/clique_network/network.edgelist')\n",
    "    insert_positions = []\n",
    "    with open('../data/simulation/clique_network/implant_positions.txt', 'r') as f:\n",
    "        for line in f.readlines():\n",
    "            if line.startswith('#'): # comment\n",
    "                pass\n",
    "            elif line.startswith('Subnetwork'):\n",
    "                positions = line.split(':')[1].strip().split('\\t')\n",
    "                insert_positions.append([int(i) for i in positions])\n",
    "    print (network.number_of_nodes(), network.number_of_edges())\n",
    "\n",
    "else:\n",
    "    print (\"Network type {} not recognized.\".format(NETWORK_TYPE))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 38 cliques in insert positions and in the network\n"
     ]
    }
   ],
   "source": [
    "# look for cliques in the network (sanity check for clique network only)\n",
    "list_of_cliques = list(nx.find_cliques(network))\n",
    "count = 0\n",
    "for c in list_of_cliques:\n",
    "    c_i = [int(j) for j in c]\n",
    "    for i in insert_positions:\n",
    "        if set(c_i) == set(i):\n",
    "            count += 1\n",
    "print (\"Found {} cliques in insert positions and in the network\".format(count))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assign Feature Vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "num_nodes = network.number_of_nodes()\n",
    "all_motif_nodes = np.array(insert_positions).reshape(-1)\n",
    "features = np.random.normal(loc=neg_distr[0], scale=np.sqrt(neg_distr[1]),\n",
    "                            size=(num_nodes, num_features))\n",
    "features[all_motif_nodes] = np.random.normal(loc=pos_distr[0], scale=np.sqrt(pos_distr[1]),\n",
    "                                              size=(all_motif_nodes.shape[0], num_features))\n",
    "not_motif_mems = np.array([i for i in np.arange(num_nodes) if not i in all_motif_nodes])\n",
    "features[features < 0] = 0 # no negative gene expression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7feac4f462b0>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.linspace(features.min(), features.max(), 100)\n",
    "fig = plt.figure(figsize=(14, 8))\n",
    "sns.distplot(features[not_motif_mems].reshape(-1), bins=bins, label='Not in Graph Motifs',\n",
    "             kde=False)\n",
    "sns.distplot(features[all_motif_nodes].reshape(-1), bins=bins, label='Not in Graph Motifs',\n",
    "             kde=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/sasse/anaconda3/lib/python3.7/site-packages/matplotlib/axes/_axes.py:6521: MatplotlibDeprecationWarning: \n",
      "The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.\n",
      "  alternative=\"'density'\", removal=\"3.1\")\n",
      "/home/sasse/anaconda3/lib/python3.7/site-packages/matplotlib/axes/_axes.py:6521: MatplotlibDeprecationWarning: \n",
      "The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.\n",
      "  alternative=\"'density'\", removal=\"3.1\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 8))\n",
    "bins = np.linspace(features.min(), features.max(), 100)\n",
    "_ = plt.hist(features[not_motif_mems].reshape(-1), bins=bins, label='Not in Graph Motifs',\n",
    "             normed=False, alpha=.7)\n",
    "_ = plt.hist(features[all_motif_nodes].reshape(-1), bins=bins, label='In Graph Motifs',\n",
    "             normed=False, alpha=.7)\n",
    "_ = plt.legend()\n",
    "fig.savefig('../data/simulation/random_network/prob_distro_similar.svg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y = np.array([1 if i in all_motif_nodes else 0 for i in np.arange(num_nodes)]).reshape(-1, 1)\n",
    "mask = np.ones(num_nodes, dtype=np.uint8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import collections\n",
    "collections.Counter(np.arange(num_nodes)[y[:, 0] == 1]) == collections.Counter(all_motif_nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(128, 710, 48, 264, 14, 79)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train, train_mask, y_test, test_mask = gcnPreprocessing.train_test_split(y, mask, 0.25)\n",
    "y_train, train_mask, y_val, val_mask = gcnPreprocessing.train_test_split(y_train, train_mask, 0.1)\n",
    "y_train.sum(), train_mask.sum(), y_test.sum(), test_mask.sum(), y_val.sum(), val_mask.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/sasse/anaconda3/lib/python3.7/site-packages/matplotlib/axes/_axes.py:6521: MatplotlibDeprecationWarning: \n",
      "The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.\n",
      "  alternative=\"'density'\", removal=\"3.1\")\n",
      "/home/sasse/anaconda3/lib/python3.7/site-packages/matplotlib/axes/_axes.py:6521: MatplotlibDeprecationWarning: \n",
      "The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.\n",
      "  alternative=\"'density'\", removal=\"3.1\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Training Features Distribution')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 8))\n",
    "bins = np.linspace(features.min(), features.max(), 100)\n",
    "_ = plt.hist(features[np.logical_and(y_train[:, 0] == 0, train_mask)].reshape(-1), bins=bins,\n",
    "             label='Negative Nodes', normed=False, alpha=.7)\n",
    "_ = plt.hist(features[np.logical_and(y_train[:, 0] == 1, train_mask)].reshape(-1), bins=bins,\n",
    "             label='Positive Nodes', normed=False, alpha=.7)\n",
    "_ = plt.legend()\n",
    "plt.title('Training Features Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Test Features Distribution')"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 8))\n",
    "bins = np.linspace(features.min(), features.max(), 100)\n",
    "_ = sns.distplot(features[np.logical_and(y_test[:, 0] == 0, test_mask)].reshape(-1), bins=bins,\n",
    "             label='Negative Nodes')\n",
    "_ = sns.distplot(features[np.logical_and(y_test[:, 0] == 1, test_mask)].reshape(-1), bins=bins,\n",
    "             label='Positive Nodes')\n",
    "_ = plt.legend()\n",
    "plt.title('Test Features Distribution')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Write to HDF5 container"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   0,    0],\n",
       "       [   1,    1],\n",
       "       [   2,    2],\n",
       "       ...,\n",
       "       [1050, 1050],\n",
       "       [1051, 1051],\n",
       "       [1052, 1052]])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "node_names = np.arange(num_nodes)\n",
    "node_names = np.vstack([node_names, node_names]).transpose(1, 0) # just stack node numbers\n",
    "node_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "network_np = nx.to_numpy_matrix(network, nodelist=[str(i[0]) for i in node_names])\n",
    "node_names = np.arange(num_nodes)\n",
    "node_names = np.vstack([node_names, node_names]).transpose(1, 0) # just stack node numbers\n",
    "\n",
    "string_dt = h5py.special_dtype(vlen=str)\n",
    "\n",
    "f = h5py.File('../data/simulation/clique_network/simulated_all_unbalanced_similar.h5', 'w')\n",
    "f.create_dataset('network', data=network_np, shape=network_np.shape)\n",
    "f.create_dataset('features', data=features, shape=features.shape)\n",
    "f.create_dataset('gene_names', data=node_names, shape=node_names.shape)\n",
    "\n",
    "f.create_dataset('y_train', data=y_train, shape=y_train.shape)\n",
    "f.create_dataset('y_val', data=y_val, shape=y_val.shape)\n",
    "f.create_dataset('y_test', data=y_test, shape=y_test.shape)\n",
    "f.create_dataset('mask_train', data=train_mask, shape=train_mask.shape)\n",
    "f.create_dataset('mask_val', data=val_mask, shape=val_mask.shape)\n",
    "f.create_dataset('mask_test', data=test_mask, shape=test_mask.shape)\n",
    "f.create_dataset('feature_names', data=np.array(np.arange(features.shape[1]), dtype=object), dtype=string_dt)\n",
    "f.create_dataset('features_raw', data=features, shape=features.shape)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make sure that Data is Correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7feaa00ef898>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HACApFAqpe/fuysnJKZ5p4PF4NGDAAE2ePNnidADKSvPmzbVt27aocafTqX379qlGjRrlev/9+/erefPmJQoem82mxo0ba+vWrSVOjvuPxYsXq1+/fsrLyysx7vF49Mwzz+j2228v18wAAKASM8PSj/Ok/dmSjMiPht2kjM6SYVgc7swZhpFjmmbWqTyXGUUAYpozZ47WrFlTXBJJUn5+vqZPn66vv/7awmSoyA4fPqyvv/66xN8rWOvOO++U2+0uMeZwONStW7dyL4kk6c0334ya0RQKhXTgwAEtXLgw5sds3rxZoVAoajw/P1/r168vl5wAAKCKMJKkJldLncZK7e+SssZKmZdV6JLodFEUAYhp/vz5Ue/WS5HTtZYsWWJBIlRkPp9Pv/3tb5WZmanLLrtMderU0VNPPRX3PXAQ7e6771a/fv3kcrmUlpam1NRUtWrVSm+//XZc7r9lyxYVFhZGjYdCIW3fvj3mx5x33nmy2aL3D/B4PLrgggvKOiIAAKiKbM7IiX9JVe8MMIoiADFlZGQoOTk5atzhcKhOnToWJEJFdvfdd2v69Ony+Xw6ceKEvF6vnn766TItI3bv3q0ZM2ZoxYoVFFCnwW63691339X69ev16quvat68eVq/fr3q1q0bl/t36dKlxObsP5WVFXt2dLdu3dSsWbMSJ8rZbDZ5PB795je/KZecAAAAVQV7FAGIac+ePWrRokXUEqH09HTt2bNHLteZn34RCoW0bds21ahRI24vRmGdwsJCpaenx5w10rp1a23atOmsrm+apsaMGaOXX35ZycnJCofDatCggRYsWKCGDRue1bVR/goKCnT++edr9+7d8vv9kqSUlBRdeeWVmjNnTqkfd/ToUd1777167733FAwG1adPH02YMEGNGzc+4yw5OTmaOHGijhw5ogEDBmjAgAGy26veu4gAAKDyOZ09iiiKAJRqwYIFGjx4sAKBgEzTVHp6uj766CNdeOGFZ3zN6dOn6/bbb1dBQYGCwaC6du2qd999V7Vq1SrD5Egk+/fvV6NGjeTz+aIeq1mzpg4dOnRW1586dapGjhyp/Pz84jGbzaZOnTpp5cqVZ3VtxMehQ4f0l7/8RR988IGSk5M1YsQIPfDAAyVmDJW3l156SQ888IAKCwsVDofl8Xh00UUXaf78+ZRFAACgwot7UWQYxhuS+krab5pm26KxmpLek9RE0nZJN5qmeeTnrkNRBCSeYDCoNWvWyOFwqH379jLOYhO3nJwcXXHFFSVmKTkcDnXq1EnLly8vi7hIQOFwWA0bNlRubm6JccMw1LdvX3300Udndf1LL700ZiHkcrn07bffqlGjRmd1fVR+R44cUWZmZtSsN4/Ho9dee0033XSTRckA6dtvv9Vrr72mvXv36tprr9XAgQPjWqICACoHK049myTp6pPGHpS00DTNFpIWFv0eQBwUFhbq2WefVceOHXXppZfqzTffjHlC0Kmw2+266KKLdOGFF55VSSRJzz77bNQLsUAgoHXr1umbb745q2sjcSUlJemFF14ocbLWf/aT+dvf/nbW1z927FjMcbvdruPHj5/19VH5LVmyJOYL7/z8fH3wwQdlfr9JkyapWbNmcrlc6tSpkz777LMyvwcqh+nTp6tDhw567rnnNGXKFI0cOVKXX365CgoKrI4GAKjEyqQoMk3zc0mHTxr+laS3in79lqTry+JeAH5eKBRSjx499Mgjj2jNmjVauXKlRo8enRAbvG7fvl3hcDhq3Ol0as+ePRYkQrzccMMNmjt3rvr06aPmzZtryJAhysnJ0fnnn3/W1x4wYEDMjdddLpdat2591tdH5ZeamhpzA3TDMFS9evUyvdcLL7ygu+66S99//718Pp+++uor9e3bl9MkEcXn82n48OHFS7WlSHm5adMmTZw40eJ0AIDKrDxPPatnmmauJBX9zI61QBzMnj1bGzZsKLG8Kz8/X7NmzdK6dessTCb17Nkz5gt6n8+n9u3bW5AI8dS1a1fNnTtXW7du1TvvvKOWLVuWyXXvv/9+ZWZmFs9YstlscrvdeuONN2IeoQ6crFu3bjE36E9JSdGIESPK7D6hUEh//vOfow4JKCgo0EMPPVRm90HlkJOTE3Pc6/Xq3XffjXMaAEBVUp5F0SkxDGOkYRjZhmFkHzhwwOo4QIW3aNEi5eXlRY2Hw2EtXbrUgkT/NXr0aNWoUUMOh6N4zOPxaMyYMWxmXcns3r1bf/nLX/Sb3/xG//rXv0psNF3W0tPTtX79eo0bN07XXXedRo0apdWrV6tfv37ldk9ULna7XXPmzFGtWrVUrVo1paWlyeVy6fHHH1fnzp3L7D6HDx8udcnQ2Z7+h8rH7XbHnIUrSWlpaXFOAwCoSsrzGI99hmFkmKaZaxhGhqT9sZ5kmuarkl6VIptZl2MeoErIzMyUy+WK2gvI4XCoXr16FqWKqF27ttauXaunnnpKn3zyiWrVqqUxY8Zo8ODBluZC2VqxYoV69+6tQCAgn8+nmTNnaty4cVq9erVq165dLvdMTU3V6NGjNXr06HK5Piq/Tp06KTc3V5999pmOHz+ubt26qU6dOmV6j/T0dDmdzpgnADZt2rRM74WKr3379qpTp47y8/NLLI30eDy6/fbbLUwGoNIKB6Xc5dKBNZIZlmq3kzK7SLboFQGo3Mrk1DNJMgyjiaSPf3Lq2d8lHTJNc5xhGA9Kqmma5tifuwanngFnb+/evWrevHnUDI5atWpp165dMZdXlGbVqlX65JNPlJaWpsGDB6thw4ZlHReVjGmaatmypb777rsS406nU6NGjdLzzz9vUTIgMTzxxBMaP358ieVnbrdb77//vq699tpSP27VqlV644035PV6NWjQIF133XVKSrJ8YjjK2ebNm9W9e3d5vV6ZpqlgMKg77rhD/+///b+zPmCiPP3444+aO3euUlJS1L9/f9WoUcPqSAB+iWlKmydLJ3ZKZmRfNBl2KaWW1G6kZLCcv6I7nVPPyqQoMgzj/yR1k1Rb0j5Jj0n6UNI0SY0k7ZA0yDTNkze8LoGiCCgbS5Ys0eDBg4vfhaxfv75mzJihdu3andLHm6ap3//+93rvvfdUWFgoh8OhpKQkTZ48WQMHDizn9KjI9uzZo2bNmkXNaJMis912795tQSogcZimqf/93//V+PHjdezYMTVo0EDPPPOMbrzxxlI/Zvz48XriiSdUWFiocDgsj8ejq666Sh988EGlL4t8Pp9mzJihLVu2qG3bturXr1+J5ctVQTAY1IIFC3To0CF17dpVjRo1sjrSz/rrX/+qp556SklJSUpKSlI4HI+LNXsAACAASURBVNb06dN19dUnH5AMIKGc2CFtflsKB0qOJzml5r+WanJASEUX96KorFAUAWUnHA5rw4YNcjqdOu+8807rnce5c+dq4MCBUbOS3G639u7dy94IKNXhw4eVkZEhv98f9Vjz5s21detWC1IBicc0Tfn9fjmdzp/9+rxnzx41bdo0arlaamqq3n///Ur94nvXrl3q3Lmzjh49qvz8fKWmpqp+/fpavnw5+9olqNWrV6tbt25RG7Z7PB7t3btXqampFiUD8Ityl0s7FkhmKPqxjMukxlfFPxPK1OkURZX7bSigCktKSlL79u3VunXr056ePmXKlJibD9vtdi1cuLCsIqISqlmzpi677LKo08bcbjd7agA/YRiGkpOTf/Hr84IFC2S3R28pmZeXp3//+9/lFS8hjBo1Srm5ucrLy5Npmjpx4oS2b9+u+++/3+poKMVbb70Vc0ZpUlKS5s6da0EiAKfMWS328rIku5TM8tGqhqIIQJSfW8pQ2Zc54OxNnTpVTZs2VWpqqlJTU5WSkqKrr75a99xzj9XRcJa8Xq9Wr16tHTt2WB2lynC73TG/7tpstko9uzMUCmnevHkKhUq+sx0IBPTBBx9YlAq/xOfzlXpSW6yZpgASSHoryeaQdNIbGIYtsqk1qhRe8QGIMnToUHk8nqjxUCikXr16WZAIVjpw4IBuueUWeTwepaam6ne/+50OHTpU6vMzMjL0zTffaNasWZowYYKys7M1ffr0mLMiUHE8//zzqlOnjnr16qVWrVqpR48eOnz4Z7ceRBkobYNrp9Op3/3ud/ENA/yCG2+8Meb3D4FAQH369LEgEYBTlmSX2gyXPPUj5ZBhl1y1pTa/k+wpVqdDnLFHEVBBmKapBQsWaNKkSQoGg7r55pvVr1+/cpnhY5qm/vCHP+jVV19VKBQqfoH/S6fyoPLx+/1q3bq1du7cqUAgsrmhw+FQ06ZN9fXXX1f58sfr9WrBggUKBALq2bNnmZ/sEwqFlJOTI5vNpg4dOlg2o2/u3Lm64YYbSuw74nA4dMUVV2jBggWWZKpKPv/8c/Xr109S5OtzIBDQP/7xD91xxx0WJytfffv21dy5c0vMKnI4HLrlllv0xhtvWJgMpTFNU0OHDtW///1veb1e2Ww2ORwO/fOf/9TIkSOtjgfgVPlPSGZYSq5udRKUITazBiqhe++9VxMnTizeO8jj8ahfv36aOnVquR2Ru2nTJs2ZM0epqakaOHAgm4eepoMHD+q1115Tdna22rdvr1GjRqlevXpWxzoloVBISUlJmj59uoYPH64TJ06UeDw1NVVTpkxR//79LUpovQULFujXv/51cXkTCAT0yiuv6NZbby2T6y9evFiDBg2Sz+eTaZqqVq2aZsyYoYsvvrhMrn86evbsqc8++yxq3OVy6bvvvlODBg3inqmqKSws1Lx581RQUKBevXpVia/Hu3fvLrGZtdvtVmZmppYvX66aNWtaHQ+lME1TS5cu1YcffiiPx6NbbrlFrVq1sjoWAFR5FEVAJbN582Z16tRJBQUFJcY9Ho/mzp2rLl26WJQMpdm2bZsuuugi5eXlKRAIyOFwyO1268svv9T5559vdbxSrVmzRrfffrtWr16t5ORknX/++crJyYl6ns1m0xNPPKGHHnrIgpTW+8+x5idv+p6SkqINGzaoWbNmZ3X9/fv3q2nTplHXr1atmnbv3h33k4PatGmjzZs3R42npaVpyZIl6tChQ1zzIHGsXLlSDz30kNatW6dzzz1XTzzxhK655poyu77f79fMmTO1ZcsWtW3bVtddd12Vn8kInDHTlPZlS3u+kIJeyZMhNe4jpVL2A1UBp54Blcy8efNibg7p9Xr1ySefWJAIv2TEiBE6cuRI8XKtQCCgY8eOacSIERYnK92OHTt05ZVXatWqVTJNU4WFhVq/fn3UCWZSZIPdqvwO8cyZM2PO5AsGg3rnnXfO+vpTp06N2sRXksLhsCUnXV111VVyOBwxH2vdunWc0yBRLFu2TD169NBnn32mQ4cOKTs7WwMHDtT//d//ldk9nE6nBg0apIcffli/+tWvKImAs7FrsbRjnuQ/JoUD0okd0qZJknef1ckAJBiKIqACSEtLi/nNscPhUPXqrB1ORIsXL445vmLFipgFQCJ44YUX5PP5SowFAoHiZWj/YbfbVbNmzSq97Cw/Pz/m/8dgMBi1TO9M7N+/P+YR036/XwcPHjzr65+uBx98UDVq1JDT6Swec7vd+vvf/y6XyxX3PEgMDzzwQIl9q6TIGxj333+/EmnGOgBJIb+U+2WkIPqpcFDatcSaTAASFkURUAEMGDAg5rjNZtPNN98c5zT4Jfn5+aW+SDJNM64bEm/ZskX9+/dXtWrV1KBBA40fP77Uomrt2rUxjy9OS0tTx44dZbPZZLfbde2112r58uWlzjApD4FAQMuWLdOqVasSomjr06dPzP/Hbre7TAq0Hj16xDw5yG6368orrzzr65+u+vXra/369br77rvVrl07XX311froo480atSouGdB4li/fn3M8f379ysvLy/OaQD8LP8xxX7pZ0r5e+KdBkCCoygCKoAaNWroww8/VLVq1Yp/uN1uTZ48Weecc47V8XASwzBK3WA8OTm53DYfP9nu3bt18cUX6+OPP9aJEye0Z88ePfHEE7rttttiPv+iiy5ScnJy1HggENC7774rv98vn8+nmTNnKiMjo7zjF5s3b57q1auna665Rr169VLDhg21cuXKuN0/lqZNm2rMmDHyeDzF/z89Ho/69++vrl27nvX1e/Toocsvv1xut7t47D8b2Hfq1Omsr38m6tevr7///e9av3695syZo549e1qSA4kjMzMz5nhKSkqJv7sAEoAjLXKKVSyu2vHNAiDhsZk1UIEUFhZq0aJFCoVC6t69e8wZB0gMV155pT7//PMSY4ZhaNSoUXr55ZfjkmHs2LF67rnnomYJlXZS1Z49e9SmTRsdP368eLZMSkqKrr76akv2xZGk3NxcNW/ePGp5S/Xq1bVr1664b+p8sqVLl2rSpEny+/266aabdM0115RZERgIBDR58mS9+eabstlsGjFihG6++ea4zkgDfs6UKVM0cuTIEp+fbrdbY8aM0ZNPPmlhMgAxfT9LOrgustzsP5IcUuvfSmmNrMsFIC449QwALPbjjz+qc+fOOnbsmAoKCuRyudSyZUt9/vnnqlatWlwydO3aVV988UXUePXq1fX++++rd+/eUY9t3rxZ9957r5YsWSK3261Ro0bp8ccfL7E3TTz9/e9/16OPPhq1d1Jqaqpefvll3XLLLZbkAhDxwgsv6M9//rN8Pp+SkpI0evRo/fWvf425CT4Ai5khacdCad/qSFmUXF1qcq2U3tLqZADi4HSKIo6OAIBy0LhxY/3www/68MMP9cMPP6h9+/bq06dPXGeDnH/++Vq+fHnUnj5+v19NmzaN+TGtW7fWp59+Go94p+TgwYNRJZEUmW1z6NAhCxIB+KnRo0frjjvu0MGDB5Wenh5z+SqABGHYpMZXSY16RYqiJIcUp+XwACoWZhQBQCW1ZcsWdejQocSyEJfLpW7dumnOnDkWJjt18+fP14ABA6I2xnW73Vq+fLkuuOACi5JVTaFQSO+//76mTp0ql8ul2267Tb17947bvlsAAAA4M6czo4iNDgCgkmrZsqU+/fRTtWnTRna7XcnJybrpppv0wQcfWB3tlPXs2VOXXXZZ1KbOAwcOpCSKs3A4rH79+um2227TrFmz9P7772vAgAEaO3as1dFQ0ZlhqeCAVHjE6iQAAEDMKAKAKiE/P1/Jycmy2yveiuNgMKi3335bkydPlsPh0O9//3vdeOONzGKJszlz5ujGG2+Mmt3lcrm0cePGUpczAlJkyWteXp7S09NLfu4e3y5tnS6FCiXTlFw1pZaDpZRalmUFAKAyYkYRAJyhcDis8ePHq169enI6nercubNWrVpldayz5vF4KmRJJEl2u13Dhg3TokWLNG/ePA0ePJiSyAKzZ8+OKokkKSkpSQsXLrQgESqCQCCgu+++WzVq1FBGRoYaNGjw31mN/uPSN1OkwAkpHJDMoFSwX9r0phQO/fyFUfkUHpK+fVdaPU766lkpd3npx7kDAMpVxXzVAADl5A9/+IMmTpxYvK/PihUr1L17d61cuVJt27a1OB0qEr/frzVr1sjtdqtt27YVvtyqWbOmHA6HAoFAiXGbzabq1atblAqJ7q677tI777yjgoICSVJubq6GDh2q2rVrq1tzI3YREPZLx76T0lvFOW05Cwel/TnSgfWSkSTV6yTVviDy66rOf1za8JoU8kkyIzPMdn4mFRyUmvazOh0AVDn8ywSgSsrPz1dOTo5yc3OLx44ePapXX321xObPklRYWKinnnoq3hFRgc2cOVP16tXTVVddpc6dO6tly5b65ptvrI51Vm699daYs9IMw1Dfvn0tSIREd/z4cb399tvFJdF/eL1ePfnkk5FywIwxc8gMS/4TcUpZzgoPR5bX+fOkzW9LOxZI+bulvJ3SD7Ol76ZbnTAx7FkemVWmn2yJEQ5IB9ZG/uwAK3n3Sbu/kPaurDxfm4BfwIwiAFXO3/72Nz355JNyOBzy+Xzq06ePpkyZoh9++EFOp1OFhYUlnh8Oh7VmzRqL0qKi2bp1q26++eYSheO2bdvUvXt37dy5M2bZsnnzZh04cEAdOnRQWlpaPOOesubNm+vNN9/U8OHDi/8b7Ha7Pv744xKbjQP/sXfv3lKXvG7btk2qdq50cENkBtHJ0hqVc7pyFiyUtrwnndgpJdmKltZJ0k9mUIUD0pEtUv5eyVPfqqSxBQsiP5KrR45UL295O2OXhkn2yEbnztTyzwCczDSlHz+V9mdL4XBk9t+O+VKzAVKtNlanA8oVM4oAVCnTpk3TU089pYKCAh0/flw+n0+ffvqphg8frsaNG8vvj37BYhiG2rVrZ0FaVESvvfZa1PIs0zSVn5+vBQsWlBjPzc1Vx44dlZWVpf79+6tevXr65z//Gc+4p2Xw4MHav3+/3nvvPX344Yfau3evOnfubHUsJKhGjWKXPUlJSbroooukmudJrnTJ+EmZlOSILDlz141TynKy7UPpxI7IvkshX9ESuxjL7MxwZMZRogj5pS3vSznPSOtflrL/HpnVU95SakuKsTw3HJKSa5T//X/C7/fryy+/1OrVqxUOs0dSlXbix8hy0XBQUjjy+RwOSttmRMpgoBKjKAJQpYwfP175+fklxnw+nz766CPZbDbdeuutUbMjUlJS9NBDD8UzJiqw3NzcqKJIipRFBw4cKDHWr18/bdiwQV6vV8eOHVNBQYEefvjhqEIpkXg8Hl199dXq3r27HA6H1XGQwFwulx5++OGYX1Mfe+yxyGyR84dLDbpGigJ3htS4j9T8BosSl5FgoXR0a+wZMiczbJLDU/6ZTtV3/5aOfBPJHg5E9gr6YbZ07PvyvW/GZZG/Dz9l2KRqTSJlYpx88sknqlevnq699lr16NFD55xzjr766qu43R8J5uCGoiWRJzOkY9viHgeIJ4oiAFXKvn37Yo7bbDYdPnxYEyZM0D333KO0tDQZhqG2bdtq9uzZ6tChQ5yToqK65ppr5PFEv/ALBoPq2rVr8e+3bNmizZs3KxgMlnie1+vVs88+W+45y9uaNWvUr18/NWzYUN26ddPixYutjgQL/PGPf9TLL7+sVq1aqUaNGurdu7e++OKL/x4OYEuWGl4ptf8f6YJRUr2sir+5c8inmLNjYjGSIjOrEkEgL3bBFQ5Ie74o33u760qtbpaSa0b+TAybVKut1PLG8r3vT+zYsUODBg3S0aNHdfz4ceXl5WnPnj3q2bNn1D5bqCrMM3wMqPgq+L/EAHB6unfvrqSk6C99brdbjRo1kt1u19NPP61jx44pEAhow4YN6tatW/yDosIaOHCgWrVqVWIWhcfj0W233aYmTZoUjx06dKjU/VtKKzQrilWrVqlLly6aPXu2du/erSVLlui6667TjBkzrI6GODMMQ7feequ++eYbHTlyRPPmzdOFF15odazy5UyT7CmxHzNsUpIz8sNZXWozNLLcLhEE8iP7KcXiO1r+969+rnThaKnTA9JFf5Ka/1qyOcv/vkXeeuutqOJekkKhkD7++OO45UACqdWulM/PsFS9edzjAPFEUQSgSnniiSdUrVq1Ektm3G63nnvuOdls//0G2TCMEr8HTpXT6dQXX3yhp59+WhdffLF69uypt956S88//3yJ57Vv316hUPTSFJfLpX79KvZx0Pfff7+8Xq9M87/vuHq9Xt17770lxoBKyUiSmvYteoFZNLPIsEXKo/Z3SW1+F1ly1+FeyZNhZdKSXDUjm/dGMaS0xvHJYBiRP6eTl6HFwf79+2PuUxgMBnXo0KG450ECqNZEqtPhv5/Lhi3yd7Pp9ZLdZXU6oFwZifQNW1ZWlpmdnW11DACV3I4dOzRu3DgtWbJETZo00YMPPlhiSRAQL6+88oruu+++4hPSXC6X6tatq7Vr1yo9PX77cpS11NTUqL3ApMgpaUeOHFFqKicYoQrIz5X2LJMKD0vVGksZnSOzjcpbOCjJKH120M/Zs0zategn+7IYkVk97W6P615BVpg1a5Zuvvlm5eXllRhPSUnRV199pfPOS5Algoi//L3S0S2RwqjW+ZKzmtWJgDNiGEaOaZpZp/RciiIAQEW1Z88eeb1eNWvWTIZxinuCJJjPP/9czz77rHJzc3Xdddfpf/7nfyp0SSRJzZo10/ffR29+6/F4dOzYMWbrAeWh4IC07SMpb1dkZk6NllLTfqe/WfbhzdLupZE9i6o1kRp2i8w2quRCoZB69uyp1atXF5f3Ho9HN998s1599VWL0yEhmaZUeDAyizC5ZuTzDkhgFEUAgCibN2/W3/72N61du1bt27fXn/70J7Vp08bqWGdk165dGjRokNasWSObzab09HRNnjxZPXr0sDpahXL48GG98sorWrJkiVq2bKm7775bLVq0OOvrvv7667r77ruLX2xJkSWeo0eP1rhx4876+gBOEvRKa56PnFL2H0aS5KolXXAnL2BPkd/v1+TJk/X2228rOTlZI0eO1A033FBh34hAOTqxU9r6vhQs2ujcWU1qOTiyMTuQoCiKAAAlrFy5Uj179lRhYaFCoZBsNpuSk5O1cOFCXXrppVbHOy3hcFgtW7bU9u3bS+zx43a79fXXX+vcc8+1MF3FsXv3bnXs2FHHjx9XYWGh7Ha7nE6nPv74Y3Xv3v2srm2apsaNG6enn35apmkqFAppxIgR+sc//lHqBt4AzkLucmnnZ9FHeSc5pVY3RTaKPlWmGZmVFDgheRpIydXLNitQ0QXypTXPSeGT9rSyp0gdxyTOBvXASU6nKGIzawCoAkaPHq38/PziYiUUCsnr9Wr06NEWJzt9S5cu1b59+6I2gg4EAvrXv/5lUaqK59FHH9Xhw4dVWBiZgRAMBuX1evX73//+rDecNgxDf/rTn3TgwAGtW7dOBw8e1PPPP09JhCpl9+7deuSRR3T99ddr/PjxOnz4cPndzLs/uiSSJJlS4WlsxOw7Jq17Udr8trRtprT2eemH2aVsco3/z96dx0VVd38A/9zZ5w6LyiaoiHuuqBDlvuVeWmYu5L6nPvwy18zKsjLcHs1yS809M7VUJCFTUxQXUFRSFDWXUgFBltmY7f7+mEdymkFZZubOwHm/XryKL3fuPcMm98z5nkMqqaxLAGeyXjcZgcfXnB8PIQ5Af7ERQkglkJycbHP9/Pnz4DjOrcrq79+/bzNevV6PP//8k4eI3NMvv/xicxT0/fv3kZGRgerVq5f7GjKZDPXq1Sv3eQhxN+fPn0fnzp2h0+lQWFiI+Ph4LFmyBElJSahd2wETxDxqANmptpNFbEDJz5O+y9x8G08lhrJSAI+agF9oucMkpELQFwCc9b+f4IyATmm9TogboooiQgipBLy9bW8d8PLycqskEQBERERAr7e+GVIoFNSjqBSKmzzGcRxYlnVyNKQkOI7Dxo0b0bhxY/j5+WHQoEG4ceMG32ERG8aPH4+CggIUFhYCADQaDXJycjBjxgzHXNC3OSCUAXjq9zkjBBSB5iRPSRTmAaoMWCSJAHPy6eEZe0VKiPvzDDZv6/w3RgB41nJ+PIQ4ACWKCCGkEpg6darVzT/Lspg6dSpPEZVdvXr1MHjwYIvnI5VKUb16dQwbNozHyNxLVFSU1feERCJBjx494OVFo39d0dy5cxEVFYW0tDQ8evQIe/bsQXh4OO7evct3aOQpGo0GFy9etFo3mUyIi4tzzEWFUqD5ePPoboHE3Csl4EXghWElb2Rt0hV/rLHQfrES4u6qNgTkfoDgqc05AjHgVddc3UdIBUDNrAkhpBIwGAyYNGkStm/fDqlUisLCQkRGRmLt2rVu2TfGZDJhw4YN+Oabb6BUKjFw4EDMnj3b7cfKO5PJZML48eOxY8cOSCQSGAwGNG3aFIcOHUK1ahV/FLa7yc3NRWBgYFFPqSfEYjEmTpyIlStX8hQZ+Te9Xg8PDw/odDqrj/n7+yMjI4OHqEqAMwHJS8wT1J7GCIHANkDwK/zERYgrelJpl3XJXEnk3xoICDP/vBDiomjqGSGEEJuysrJw69Yt1K1bF35+fnyHQ1zA3bt3kZKSgtq1ayM0lHqQuKrExET07t0beXl5Vh8LDQ1FSkoKD1GR4kRGRmLPnj0WySK5XI4ZM2bg008/5TGy53h83Tzy22QAwJmrJMQKoPlEc5USIYQQt1WaRJH7vYxMKo24uDisWLECWVlZ6NevH6Kioorts0IIKRk/Pz9KEBELwcHBCA4O5jsMC3fu3MF///tfJCUlITQ0FO+9916lb4pdq1aton43T2MYBg0aNHDINfV6Pfbu3YuYmBj4+flh3LhxaNKkiUOuVdGsWrUKt27dQmpqKoRCIfR6PV555RXMmzeP79CerWpDc1Io4xxQmAt41zM3sRZK+Y6MEEKIE1FFEXFJ0dHRWLBgAVQqFQDz5JzAwECkpKRQ7wxCSIWm0WiwcuVKbNu2DRKJBBMnTsSYMWMgFFaOcvbLly+jXbt20Gq10Ov1EIlEkMlkOHLkCF588UW+w+PVa6+9hsOHD1tsP2NZFr///jvCw0v0AmGJFRYWomvXrrh48SJUKhVEIhHEYjHWr1+PyMhIGI1GMAwDgYDaXT7L+fPncePGDbRo0QIvvPAC3+EQQgipxEpTUUT/utsRx3H47bffMG7cOEycOBEJCQl8h+QUHMfhwoULSEhIsPlqZ2nl5eVh/vz5RUkiANBqtXj48CHWrl1b7vMTQor3/fffo0GDBpBKpWjWrBkOHjzId0glYjQaoVKp4EovfpSFwWBAhw4dMH/+fFy+fBnJycmYNm0aIiMj+Q7NaaKiolBQUFA02c5gMECpVGLy5Mk8R8a/nTt3YsCAAZBKpZDJZAgKCsLOnTvtniQCgK1btyIlJaXo32KDwQCNRoNx48ahU6dOkEgkkMvlGDZsGHJzc+1+/YqidevWGDRoECWJCCGEuBWqKLKjiRMnYvv27VCpVGAYBnK5HFOnTkV0dDTfoTnM1atX0bdvX2RlZUEgEIDjOGzYsAFvvfVWmc95+PBhDBw40GYfhg4dOuD48ePlCZkQUoxNmzZhypQpUKv/aWQql8vx448/om/fvjxGVjyj0YgPP/wQK1euhFarRVBQEFasWIHXX3+dl3jS09MRGxsLlmUxYMAA+Pj4lOrxe/bswahRo6BUKi3WWZZFYmIiWrRoYc9wXZJEIilKEj2NYRgYDAaqYAGgUqmQn5+P6tWrgynpRKtS6tatG44cOfLc4yQSCZo2bYrk5GSHxUIIIYSQ8qOKIh6cO3cO27ZtK3rljeM4qNVqrFy5EteuXeM5OscwGAzo2rUrbt++DaVSifz8fBQUFGDUqFFIS0sr83n9/PxgMBis1hmGQVBQUHlCJoQUg+M4zJ071yJJBJi3Qc2ZM4enqJ5v+vTpWLFiBZRKJQwGA+7evYu3334bx44dc3osH3zwAUJDQzFnzhxMmzYNtWrVwoEDB0p1jqNHj1oliQDz1+fkyZP2CtWujEYjfv75ZwwfPhzvvPMOyvuCj6enp811uVxOiYj/USgUCAwMdOjno7ivw7/pdDqkp6fj1KlTDouFEEIIIc5FiSI7iYmJgUajsVo3mUyIjY3lISLHO3LkiM2tHjqdrlxbxFq0aIE6depY9eOQy+X4v//7vzKfl5DnuX37NiIjI+Hv74+GDRti1apVbr+VqaR0Ol2xI5vT09OdHE3JqFQqrFu3ziq5pVarMX/+fKfGcurUKSxfvhwajQZarRYqlQoajQZDhgxBQUFBic9Ts2ZNSKXWTWNFIhGqV69uz5DtwmQyoX///hg2bBi2bduGdevWoVOnTvjvf/9b5nO+8847kMstpyvJ5XKMGzeOEkVONGnSJCgUihIdy3FchX1RjBBCCKmMKFFkJyzLQiwWW60LhcIS/6HlbrKzs22uGwwGPHz4sMznZRgGv/zyC5o3bw6WZeHl5QUPDw989dVXaNOmTZnPS8izPHz4EGFhYfjhhx+QlZWF9PR0zJw5s9IkJyUSCapVq2bzY7Vr13ZyNCWTkZFR7DakGzduODWWrVu32nyxQCgU4tChQyU+z8iRIyESWQ4kfbKV2d7b//R6fbkToTExMfj999+LqmlNJhPUajXmzp2LrKysMp3z448/Rv/+/SGTyeDt7Q2ZTIZevXpV6G3crqhXr16Iioqymbi0pWnTpg6OiBBCCCHOQokiOxkyZIjNiTQcx2HAgAE8ROR4HTp0sNlHQqFQlPuGpmbNmrhw4QLOnz+PQ4cOITMzE2PHji3XOQl5luXLl0OpVMJkMhWtqdVqfPvtt8jMzOQxMudgGAYfffQRWJa1WGdZHlZ/SAAAIABJREFUFp999hlPUT1bjRo1bFaYMAyDli1bOjUWo9FYbNLFaDSW+DyBgYE4ePAgAgMDoVAowLIsGjZsiGPHjkEikZT4PCaTCcuXL0edOnVQtWpVvPnmm0XJsx9//BEhISGQSqXw9fXFkiVLypww2r17t82tcmKxGIcPHy7TOcViMb7//ntcv34du3fvRlpaGvbu3QuZTFam85Gy++KLL7B+/XqrCq+nSaVShIaGIiIiwm7Xzc/Px7p16zBr1iz8+OOP0Ol0djs3IYQQQkqA4ziXeQsLC+Pc2bZt2zi5XM55enpynp6eHMuy3P79+/kOy6FmzJjBKRQKDgAHgGNZlgsLC+MKCwv5Do2QUmnTpk3R9/HTb97e3tzhw4f5Ds8pTCYT9/XXX3N+fn4cwzBcjRo1uC1btlgdp9VquW3btnEzZszgvv32W66goICHaM2++OILi99BT34PJScnOzWO3377zSoOAJxcLudycnJKfT6j0cilpqZy169f50wmU6kfP2nSJI5l2aI4BAIBV6VKFW7z5s0W608+X1988UWpr8FxHDdlyhROIBBYPW8vLy9u3759ZTonHx4/fswplUq+w3BJly5dsvqeefImFou5qVOn2vVzd/XqVa5atWpFP08eHh5co0aNyvRzRAghhJB/AEjiSpiboalndpabm4u4uDgIhUL07NmzxM0g3RXHcThw4ABWr16NgoICDBkyBGPHjn3mq4+EuKJRo0Zh27ZtVtUfcrkcly9fRr169XiKjB96vd7mdtqsrCxERETg0aNHUCqVRVUviYmJvHyOuP9NWly4cCEePnyIVq1aYcmSJXj55ZedHseTyZcajQYikQgikQhr1qzBiBEjnBpLRkYGateujcLCQot1iUSCKlWq2KyQ8/b2RnZ2ts3K2Gc5f/48OnToYNUnytvbGw8fPnT5KqCkpCSMGjUK169fBwD06NEDmzZtgq+vL8+RuZbw8HBcunTJooqYZVmcPHnS7tV7L730Es6dO2dR5SaRSDBx4kR89dVXdr0WIYQQUpmUZuoZJYoIIQRAamoqXnrpJYsbXqlUivbt25d5C01FNHLkSOzYscNiMqFAIECnTp1KNEq7ojt79iz2798PhUKBoUOHIiQkxOkxHDlyBAMGDEBeXp7Vx4RCoc2tcBKJBA8ePCi2T9WzrFixAnPmzClKLAoEAsTGxqJt27alD96J7t+/j0aNGllsnROLxWjcuDFSUlKocfZTMjMzMWjQIJw5cwYikQhSqRTr1q2z+9b6vLw8+Pn52dzW7ufnVym2ARNCCCGOQokiQggpg/j4eIwfP75o+le/fv2wfv16eHl58RyZ6/Dy8rI5xUsoFEKtVpeqjw5xjFu3bqFp06bQarUW60KhEFWrVsWjR4+sHlOtWjVkZmaWuqLoiaysLBw5cgQKhQLdu3cvcQNkZyksLMSaNWuwefNmCIVCjBs3Dn///TcWLVpkVXnl4eGBuLg4l0908eHBgwfIzc1Fw4YNy/y98iwFBQXw8fGxmSgKDAzE/fv37X5NQgghpLIoTaJI9PxDCCGkcujRowdu376NzMxMeHh4VNiJheVR3M0hwzBUgeEi6tati06dOuHYsWMWSRCpVIro6GhMnTrVYkIby7L45JNPynXj7+fnh8GDB5crbkcxmUzo3r07kpKSip73lStXUKVKFask0RN//vknJYpsCAwMRGBgoMPO7+npibZt2yIhIcGi8k0mkzl9CychhJASyr8DZKea/9+3BeBZi994iF3Q1DPiEGq1GrNmzUJAQACqVauGsWPHlnlUMiHOxDAMAgICKElUjMjISKtqEZFIhF69etnsaUT4sXv3bgwaNAhSqRQSiQT169dHTEwMxowZg3379qFFixaQSqUICQnBN998g6lTp/IdssPEx8fjwoULFskxtVqNrKwsmz2UjEYjWrVq5cwQyVO2bNmCwMBAeHp6QiKRwMPDA6Ghofjoo4/4Do0QQsi/3T4EpG0DMs6Z365uAe7+yndUxA5o6xmxO47j0KFDByQnJxdtfRCLxQgKCsLVq1ep0XUFp9Vq8eDBAwQEBFiNWre3zMxMfPvtt7hw4QLCwsIwfvz4cjWhvXLlCjZs2IDs7Gy89tpr6N+/P0QiKrx8Wn5+Pjp37oz09HTodLqiEeunTp1C9erV+Q6vwuA4zi4VWlqtFhqNBlWqVKm0FV9z587FwoULrdZFIhFYloVarS7quSWXy9G9e3fs27fP2WGSp+j1esTExODPP/9Eq1at0Llz50r7/UsIIS5L9RD4Yz1gMliuC0RA84mA3I+fuEixaOsZ4VViYiJSUlIs+mPo9XpkZ2dj165dGDlyJI/REUfhOA6ff/45oqOjwXEcTCYTJk+ejOjoaIf0skhLS0ObNm2g1Wqh1WoRGxuLxYsX48yZM2jQoEGpz7dt2zZMmDABer0eBoMBe/bswYsvvoi4uDiqlHmKl5cXkpKScOTIEVy+fBkNGjRAr169KKFmByqVCtOnT8fWrVtRWFiITp06YdWqVWjUqFGZzymTyVx+8pijBQUFQS6XW1QUAebPzeeff47k5GQcOHAAcrkcEydOxOzZs3mKlDwhFovxxhtv8B0GIYSQZ8m9DpisB2SA44DH1ylR5OaooojY3apVqzB9+nSrRqoAMGXKFHz99dc8REUcbc2aNZg+fbrF1DCWZTFr1ix8/PHHdr9e165dcezYMYsRygzDoEePHjh06FCpzqVUKhEQEGA14lssFqN///749NNP0bhxY7vETUhxOnfujNOnTxf1zWEYBt7e3rh27Rr8/f15js59ZWdnIyQkxGK6GQBUqVIFf//9d7GVj3fv3sXNmzfRuHHjSlstl5OTg5UrVyI2NhZBQUGYNm0aOnbsyHdYhBBCXMH9U8C93wDuX8kiRgTU7g5Uf4mfuEixSlNRRD2KiN3VrVvXZgUGy7LlemWcuLYvvvjCKtGiVquxbNky2DshzXEcfv/9d6vzchxXphHtx48ft7mu1+uxZ88ehIWF4ZNPPilTrISUREpKCs6dO2fRXJnjOGi1Wnz77bc8Rub+fHx8EBcXh6CgICgUCigUCtSpUwdHjx61mSTSaDTo378/GjVqhDfeeAN16tTB2LFjLZorVwbZ2dkIDQ3Fl19+ibNnz+Lnn39G7969sW7dOr5DI4QQ4gp8mgIoZltwtSZODYXYHyWKiN11794d/v7+FltRGIaBVCrF8OHDeYyMOFJmZqbNdaVSaXPUcXkVN367tGO5b9++jXHjxlkluZ7gOA4ajQbR0dFITU0tdZyElERaWprNLZparRbnz5/nIaKKpW3btrh37x5Onz6Nc+fO4ebNm2jZsqXNY6dNm4b4+HhotVrk5eVBq9Vi586dWLRokZOj5tfy5cuRlZVlUR2sVqsxffp0q218hBBCKgjVA+D6LuDiN8DNfYA2u/hjpd5A3X7mCiKBxPzGiIB6bwAST+fFTByCEkXE7oRCIRISEtC9e3eIxWKIRCJERETg5MmTqFKlCt/hEQcJDQ21uR4SEgKJRGLXazEMg2HDhlklhaRSaal7YL3++uvIyMh47nE6nQ579uwp1bkJKanGjRvbrFiRyWQICwvjIaKKRyAQoFmzZmjcuHGxjZGNRiO2bNlitXVarVZj5cqVzgjTZRw8eNCiwu0JgUCAS5cu8RARIYQQh8q7CfyxEci5AmiygKwU4NJac9Pq4vi1AMLeA+q+an4Lmw74NnVezMRhKFFEHKJ69eqIjY1FXl4ecnNzcfr0aerxUsEtW7bMahsHy7JYsWKFw64XEREBlmXh6ekJlmXRpk2bUr3qf+PGDVy/fh0mk+m5xzIMQ1N3iMOEhoYiIiLCIvnJMAzkcjnGjx/PY2SVi16vh06ns/mxvLw8J0fDr4CAAJvrer2+XNMlCSGEuKg/DwKmp3cBcIBJB9yJf/bjRCzg28L8JqLp1hUFJYqIQ8nlcigUCr7DIE7Qrl07HDt2DL169UJQUBA6d+6M2NhYvPrqqw65noeHB44fP46EhASsXbsWp06dKrbnSHGUSmWJp3WJxWK89dZbZQ2XkOeKiYnBuHHjoFAoIBKJ8Morr+D06dPw86OpIc4ik8nwwgsvWK0zDFPpmjhPmzbN6vepSCRC8+bNUa9ePZ6iIm6DM1mPzCaEuC6jDtDm2v6Y8p5zYyEugaaeEUIqLYPBgICAAOTk5Fisi8VimEwmiMVicBwHhmEwf/58GptNKg2j0Yjc3Fx4e3uXOJlaUSQkJKBnz54oLCyE0WiEWCyGXC5HYmIimjSpXM05ly1bhnnz5kEsFsNgMKBJkyY4cOBApZ0CR0rAZADu/ApkJZvHZst9gTp9Aa8QviMjhDwLZwLOfWE7wSvxAlq/5/yYiN2VZuoZJYoIIZXa/v37MXToUOh0OhgMBrAsi1q1amHv3r04fPgwDAYD+vfvT6+gk0pj9erV+OCDD6BWqyGRSDB9+nR89NFHlWrrZVpaGpYuXYrU1FRERERg+vTpCA4O5jssXhQUFCAlJQX+/v40uZQ8X/qPQM41gHvqZlMgBpqNA1jb2xkJIS7iz4NA5gXrn99aXYHANvzFReyGEkWEEFIKaWlpWL16Ne7du4eePXti+PDhpdrCRsyOHTuGNWvWIC8vD4MGDcLbb79t90bmxLG2b9+OCRMmWEwBZFkWH3zwAebOnctjZIQQl6crAC6ssLzJBAAwgG9zoP4AXsIihJSQyQDc/BnISQMEQnNVYEA4ULsHwFDHmoqAEkWEEEKc6vPPP8cXX3xRlGBQKBQIDQ3FsWPHIBaLeY6OlFTDhg2Rnp5ute7t7Y2cnBwIBPSHIiGkGAV3gbTtgNF6Wh7Y6kCLSc6PiRBSejoloMsFZD7UnLqCKU2iiP7iI4QQUi4ZGRn47LPPLKpQVCoVLl68iN27d/MYWcVgMplgNBqdcq2//vrL5rpSqbQaGU9IpcJx5lfXXRzHcU77fWFF5lPM54gBPGo4PRxCSBlJPACPmpQkquQoUUQIIaRcjh8/brNqSKVS4aeffuIhoorh8ePHiIyMhFwuh1QqRZcuXWxW+9hT06ZNba4HBARALqc/GEklZDIAtw+Zm7yeXQBcXAXk3+Y7KitarRZRUVFQKBQQi8Vo3bo1zpw549wgxArAL9Tc0+RpAjEQ1M65sRBCCCkXShQRQggpF29vb5uNjoVCIXx9fXmIyP1xHIcuXbpgz5490Ol0MBqN+P333/Hyyy/j8ePHDrvu4sWLrRJCLMti8eLFFbaZdX5+Pnbu3ImtW7ciKyuL73CIq7m5D8hMAkx68/uaTPP2KnUGv3H9y9tvv43169dDo9GA4zhcuHAB3bp1c3hy2UqdvkCNjoDYA2BE5mlnTccAsmrOjaMyMmiAB6eBWweAzPPmceeEEFJGlCgihBBSLl27doVMJrNal0qlmDBhAg8Rub8TJ07g5s2b0On++UOf4zhotVps3rzZYdft3LkzDh06hLZt28Lb2xstW7bEzp07ERkZ6bBr8ikmJgaBgYGYMGECJk+ejODgYKxdu5bvsIir0CmBnCvW46JNBuDvBH5isuHu3buIjY2FRqOxWC8sLMSSJUucGwwjAGp0AMJmAC/NA5qMAhTVnRtDZaR5BFz4Crj3G5CZDNz+Bbj4tbnBOCGElIGI7wAIIYS4N5FIhPj4ePTu3RtKpRIMw0Cv1+Orr75Cy5Yt+Q7PLV2/fh0mk8lqXa1W49KlSw69dseOHXHy5EmHXsMVPH78GIMHD7borQUA06ZNQ+fOnWkUPAEKHwMCEWDV84czVxa5iBs3bkAqlVr1ETMYDA7/fUFcxK19gPGpRKFJD+iMwN14oP6b/MVFCHFblCgixA1xHIeCggJ4eHjQFCLiEkJDQ3Hv3j0kJiZCqVSiXbt28PT05Dsst9W0aVObW70UCgXCw0s0rII8x759+2z+/tTr9di+fTs+/fRTxwbAcUD+LeBxOiCSAb6hgKyqY69JSkdWzbqaCADAAIogp4dTnBdeeAGFhdaTxsRiMV588UUeIiJOZdIDBbYGEZiAnGtOD4cQUjHQHSYhbmb9+vUICAiAr68vqlWrhkWLFoHjOL7DIgRCoRDt27dHnTp1cPXqVZs3LqRkXn75ZbRo0QJSqbRoTSgUwsPDA8OHD+cxsopDq9XanA5lNBqttvDYHWcCru8Eru0EHp4G/j4BXPoGeJTq2OuS0hErAP9WxTRnbs9PTDYEBQVh0KBBVv3FZDIZ3nvvPZ6iIs7DAMX1kGOEzg2FEFJhUKKIEDfy/fff4//+7/+QlZUFvV6PvLw8fPLJJ1i6dCnfoRGCu3fvIjQ0FK1bt0b37t3h5+eH7du38x2WW2IYBvHx8Rg/fjy8vb0hl8vx+uuv49y5c1SpZSe9e/e2mWRnWRavv/46ACA9PR0LFy7EggULkJpqxyROThqQd+ufBsmc0Vy5cmsfNaB1NSF9/tecWWG+6fasDTQdDch9+I7MwoYNGzBr1iz4+vpCKpWia9euOHnyJEJCQvgOjTiaQARUaQir2zpGaJ5CRwghZcC4UiVCeHg4l5SUxHcYhLishg0b2pxgUrVqVWRnZ1fYqUTENXEchzVr1mDhwoXIzMwEwzDQ6XQWvXVYlsWJEyfQunVrHiMlxLbPP/8cn3/+OQoLC8FxHFiWxZAhQ/Dtt9/iq6++wvvvvw+DwQCO4yAWizFr1izMnz+//Be+thN4nGa9LpSa+4lUbVj+axBCKg+9CvjjO0CXb65YZBiADQAajwCEEr6jI4S4CIZhkjmOK1EPA0oUEV6dP38eO3fuBMdxGDx4MPXeeA65XG7VrBIwb0lRKpU2J08R95OSkoK5c+fizJkzqFGjBubNm4dBgwbxHZaVTz75BIsWLbJqBvw0gUCAkSNHYuPGjQ6P5/bt27hy5Qrq16+Phg3pRpuUTHJyMrZu3YrCwkIMHjwYnTp1wr1799CoUSOr37dyuRxnz55Fs2bNynfR9B+B7D+s1wVSoOEgoEq98p2fEFL5cCYg/09AkwMoAgCPWsVvSSOEVEqlSRRRM2vCm/nz52Px4sVFf4ivWrUKUVFRWLhwIc+Rua7GjRvjwoULVusBAQEWvUycjeM47N69GytXrkRBQQHeeustREVFwcPDg7eY3NXly5fRvn17qFQqAEBOTg5Gjx6Nhw8fIioqiufo/qHVarF48eJnJokAwGQy4e+//3ZoLHq9HsOGDcP+/fshlUqh0+nQsWNH7N27FyzLOvTaxLb8/HzExsZCr9ejd+/e8PX15TukYoWFhSEsLMxibf/+/TaP1el02LNnT/kTRX6tgcfX/9l69gTDAF61y3duQkjlxAgA73rmN0IIKSfqUUR4cf36dURHR0OtVsNkMsFkMkGtVmPFihX27QNRwSxatMiqWSXLsoiOjuZ129l7772H0aNH48SJE0hJScGCBQsQERHh+IawFdC8efOski9qtRoffvghdDrX6V1S0uSPXC5H37597XZdlUqFjRs34v3338euXbug0+mwYMECHDhwAFqtFnl5edBoNDh27Bjeffddu12XlFxMTAwCAwMxYcIETJ48GbVq1cK6dev4DqtUBAKBzd+pDMPYZ9Kkd13APxxgROY3gcT81miIud8IIYQQQgiPaOsZ4cXSpUsxd+5cqxtfoVCITz/9FHPnzuUpMtd3+PBhvP/++7h69SpCQkKwYMECvPHGG7zFc+/ePTRs2NBqi4ZCocCKFSswduxYniJzTzVq1MD9+/et1hUKBVJTU12mMalKpYKfn98zk4EymQy1atXC+fPn7VJddvPmTbRp0wZqtRoqlQoeHh6oXr06Hj9+jOzsbKvjpVIp1Gq1fW7sSYnk5OSgZs2aVt8XcrkcKSkpbrMl8P79+6hXr57NrWfnz5/HCy+8YJ8LabOB3FuASApUbWTuUUQIIYQQ4gCl2XpGfz0TXojFYps3b0KhEBIJNd17lldeeQXnzp2DUqlEamoqr0kiAEhMTIRYLLZaV6lUiI2N5SEi91ZcIshoNLrU9h2FQoFJkyZZbe2SSCQICwtD69atMW/ePCQlJdltC+KYMWOQnZ1dtC1PqVTizp07yM3NtXm8Xq+HwWCwy7VJyezbt8/m73a9Xo8dO3bwEFHZBAUF4euvv4ZMJoNMJoNUKoVMJsOCBQvslyQCAJkPUP1FwLcFJYkIcRU5acDFVcDZL4DL68wTCgkhpJKh+mbCizfffBOzZ8+2WhcIBHjrrbccck2tVotdu3YhISEBdevWxejRoxEQEOCQa1Um/v7+NtdFIhFq1arl5Ghcj1arxe3btxEYGAhvb+/nHj979mwMGTLEoiJDLpdj5MiRLtfzafHixfD09MTy5cuhVCpRp04drFixwq5bzZ7QaDQ4deqUxUQ1wJyAEIlEYBjGatR5q1atKPHsZFqt1uprBJgTnU8SfO5i7Nix6NWrF3766ScYjUb079/fZSr6CCEOknUJ+PPAP/3DVPeBazuAhkOpyTwhpFKhrWeEN1u3bsWECRMgFAoBmG8kvv76a4dsVcrNzUVERATu378PlUoFmUwGkUiE3377DREREXa/XmViMplQo0YNPHz40GJdJBLh8uXL9n313c1ER0dj/vz50Ov1MJlMaN26NeLi4uDj42N1bEJCAiZNmoSrV69CKBRCKBSC4zgIBAKMGzcOS5cutVm55Qo4joNer3doUkar1cLT09NmhZCXlxe0Wq3VVtYdO3Zg6NChDouJWLt9+zYaN25stWWLZVn8+uuvaNu2LU+REUIqDYMGKMwDpFUAUTHTYDkToHoAmAyARw1zbzCOA84vA/QF1sezAUCLdxwbNyGEOBhNPSNuYfjw4ejVqxdiYmLAcRxeffXVYqtTyuuzzz7DnTt3im4kn9zEDB8+HGlpabw2gnZ3er3e6qYQMFeH6fV6G4+oHHbs2IEPP/zQ4nOQnJyMBg0a4K+//rLYsnX16lX07NmzqIm1yWSCSCRCly5dsHfvXshkxfyh6yIYhnF45Y5MJkO3bt1w+PBhGI3GovUnTYefXnti7ty5GDJkCP18O1FISAg++OADLFy4EFqtFhzHgWVZDB06FG3atOE7PEJIRcaZgNu/AJkXAEYIcEbAvzUQ0ss8EewJ1UNzlZBB+8/4+HpvmCuG9Erb59ZY98EjhJCKzOE9ihiG6cUwzDWGYW4wDDPH0dcj7sXPzw+jR4/GmDFjHJYkAlA0Henf7t69a7NxMCm5X3/91eZNutFoxIYNG3iIqPQMBoPdJ4p9+umnNhNljx8/xnfffWextmTJEhQWFlqsaTQaHD16FFlZWXaNy51t2LABNWrUgKenZ1EloslkQl5ens3vwUePHuHSpUvODrPSmzdvHo4fP46pU6diwoQJiImJwbp16yhhRwhxrL+PA1kpAGcATIXm/2ZdAP5O+OcYkwG4uhnQ5QMmHWAsNL/d2A0UFhTfK0zi5ZznQAghLsKhiSKGYYQAvgHQG0ATAEMZhmniyGsSYotUavsffo7jqIdJOeXl5Vn1hgHMiaKcnBweIiq5nJwcDBo0CCzLQi6Xo23btrhy5Ypdzv2s8fEHDhyweD81NdVmokMqleLWLfdsonnr1i3MnTsXI0aMwI4dO+ySiKtRowZu3LiBTZs2wdPT87nHMwxjs9qNOF5YWBhWrFiBNWvWoHPnzrwkie7fv4/o6GhMmzYNMTExNn/GCCEVyIPT//QWesKkBx6e/uf93HTAZON3AWcyJ5VqdAAE/9rmLRADNTvbPVxCCHFljq4oigBwg+O4WxzH6QDsBNDfwdckxMqECRMgl8st1oRCIcLCwuDn58dTVBVDly5dbFbOeHh44PXXX+chopLhOA5du3bFzz//XNRD6PTp02jbti0ePXpU7vM3b9682I/VqVPH4v2IiAib/Ye0Wq1b9niKjY1F8+bNsWTJEmzduhUTJ07ESy+9VLS1rjzEYjHatWtnNX7dFpFIhNatW5f7msT9HD58GA0aNMDHH3+M5cuXY+jQoejSpYvdKwcJIS6C4wBjMS8MGDT/+n8b/Vk5E2BQAYFtgRqdzJVFjAAQsUDtnoBfC4eETQghrsrRiaIaAO499f5f/1sjxKneffdddOvWDSzLgmVZeHp6okaNGvj+++/5Ds3tBQUF4YMPPgDLskVVAwqFAhEREejXrx/P0RXv5MmTuHnzpkWSi+M46HQ6bNy4sdznX716tc0qCrFYjClTplisTZ8+HTKZzOJ4lmUxbNgwt5vMZzAYMHz4cKjV6qLPrVKpxLVr17Bq1Sq7XON5098kEglYlsW2bdtctgE4cRyDwYAhQ4ZArVYXbelUKpVITk52m+2whJBSYhhzw2lb2Or//L9XiDmp9G8CCVClgfk8NdoD4bOBsFlA2AwgoER9XwkhpEJxdKLIVq25xW9nhmEmMAyTxDBMEvXiII4iFotx4MABnDx5EsuXL8euXbtw69YtBAcH8x1ahfDhhx/il19+QWRkJPr164d169YhLi4OIpHr9stPT0+3uWVOo9EgNTW13OcPDQ3FoUOH4OnpCYZhIBQKoVAosG3bNjRr1szi2JCQECQmJuKVV14By7KoXr065s2bh7Vr15Y7Dme7ePGizQozjUZjt8SsQqFAv379rLaUSqVStG/fHnPmzMEff/yBPn362OV6xL1cuHDBZuWQWq3Gli1beIiIEOIUIX3+tW2MMb9fp/c/S7JqgH8ry+MEYnOSqWrDpx4qME9MYxzezpUQQlySo+/i/gJQ66n3awKw6BzMcdw6AOsAIDw83EaKnxD7admyJVq2bMl3GBVSx44d0bFjR77DKLEWLWyXkbMsi4iICLtco0ePHsjLy0NaWhry8/PRqlWrYntiNW3aFPHx8Xa5Lp9YloXJZLL5MYVCYbfrrF+/HgMGDMCpU6cgkUig1WoxYcIErFixwu2bJufl5UGr1cLf39+hz0Wj0eDHH39ESkoyTAm/AAAgAElEQVQKGjdujKFDhz63WssdiMVim0lgANSTjpCKzKs20HQM8NdxQJNhriSq0RFQVLc8LqQP4F0XyEgy9zDybQH4tTRPSiOEEAIAYIr7Y8ouJ2cYEYDrALoB+BvAOQCRHMf9Yev48PBwLikpyWHxEELI07p06YLTp08XNTwWCoXw9fXF9evX4eVFE07KguM4vPDCC1YVWwqFAuvXr8eQIUPser2bN2/i7t27aNq0qUMnJzpDZmYmhg8fjmPHjoFhGAQHB2Pz5s0lGiufkpKC1atXIyMjA/369UNkZCRkMpnFMUajEatXr8Y333yDvLw8FBQUgOM4qFQqKBQKsCyL06dPo27dus+9nsFgwI4dO7B582ZIpVKMHz8er7/+uksk6TiOQ+3atXHv3j2LdYVCgbVr1+Ltt9922LWVSiXOnz+PatWqoWnTpiX6fFy5cgUPHjxAq1atUK1aNYfFRgghhJDKjWGYZI7jSrSf1qGJov8F0wfAcgBCABs5jvu8uGMpUUQIcSaNRoMPP/wQmzZtQmFhIfr06YOlS5eiZs2afIfm1q5du4YuXbpAqVSC4zgYDAaMGjUKq1atcolEgiviOA7NmzfH9evXLbbueXh44MqVK6hVq1axj92yZQsmTZqEwsJCmEwmKBQK1K9fH6dOnQLLskXHDR8+HHv37i22qbhAIEDXrl3x66+/PjNWk8mEPn36ICEhASqVCoA5CRMZGYl169aV5mk7zIULF9CtWzcYDAbo9XowDIM333wTmzdvhkDgmK0kq1evxowZMyASiWA0GhESEoLY2NhitzhnZWWhT58+uHLlCsRiMQoLCzFjxgx8+umnZfo5KSwsxM6dO3Hw4EEEBgZi4sSJaNKEBs0SQgghxMylEkWlQYkiQgipGAwGAw4fPoyMjAx06NChRFUqldnJkyfRq1cvKJVKi3WJRIKZM2fis88+s/k4tVoNf3//ooTNEyzLIjo6GlOnTgVgrrxq1qxZUfVccYRCIbRa7TP7i8XFxWHgwIFWscrlciQlJblMckKj0WD//v3IyspCp06dnjmJsLwSEhLQs2dPiyScUChEo0aNkJqaajPx07lzZ5w8eRIGg6FoTaFQYNOmTRg4cGCprq9Wq9GuXTukp6dDpVJBKBRCIpFg06ZNGDRoUNmfGCGEEEIqjNIkiqhDGyGElJJWq8XPP/+Mbdu24cGDB3yH45JEIhF69eqFkSNHUpKoBO7cuWMzmaDT6XDt2rViH3fu3DkIhdZ9NdRqNX744QeL40oyAY5hmOdWs8THx1sliQBzVdSRI0eeew1nkcvlGDx4MKZOnerQJBEAfPXVV9BoNBZrRqMRd+7cwaVLl6yOv3//Ps6cOWORJAIAlUqFZcuWlfr669atw7Vr14oShkajERqNBuPGjSua/EYIIYQQUlKuO5KIEFJhmUwm/PGHuVVZs2bN3Go7UmJiInr37g2TyVS0reqjjz7C+++/z3doz2U0GnHgwAHEx8fD398fo0ePRu3atfkOiwAICwuzShoA5sqgTp06Ffs4T09PGI1Gmx97ut9NcHBwsQ2enxCJRHjttddsJp6e5uvrC4lEYjVZTCQSVdoeOw8fPrT5+RUKhcjOzrZaz83NLbZq69GjR6W+/g8//GCVqALMib/k5GS0bdu21OckhBBCSOVFFUWEuAmTyYRjx45h06ZNuHz5Mt/hlNnZs2dRu3ZttG3bFm3btkVwcDDOnj1bqnOoVCosX74cHTp0wBtvvIHffvvNQdFa0ul06Nu3b1EjYKVSCa1Wi88++wyJiYlOiaGsCgsL0alTJwwfPhyrV6/GwoUL0aRJExw8eJDv0AiARo0a4dVXX7XoKSQWi1GtWjWMHDmy2Me1atUKAQEBVslWhUKByZMnF73fpk0b1KpVy2ZyQiKRwNPTEyEhIVizZs1zYx0+fLjN8wgEAvTv3/+5j6+I+vXrB7lcbrWu1+sRHm5d4d2wYUObFV4SiQSvvfZaqa/v7e1tc91oNFaISXaEEEIIcTKO41zmLSwsjCOEWHvw4AHXsGFDzsPDg1MoFJxcLudee+01TqfT8R1aqeTm5nJeXl4cAIs3Ly8vLjc3t0TnUKlUXNOmTTm5XF70eJZluejoaAdHz3GxsbE242cYhhszZozDr18eq1at4liWtYq9SpUqbvd9VFHp9Xpu8eLFXN26dbnq1atzkyZN4jIyMp77uGvXrnE1a9bkPD09OS8vL04mk3Hz58+3Ou7Bgwdcly5dOKlUysnlcq527drc0qVLueXLl3OxsbGcwWAocawxMTGcl5cX5+XlxXl6enL+/v7c6dOnS/V8K5L8/Hyufv36Vr+Xli1bVuxjfvjhB45lWU4gEHAAOJlMxgUGBpboa/5v+/bt4xQKhdXvpfr163Mmk6k8T40QQgghFQSAJK6EuRlqZk2IG+jRoweOHj1qsTVFLpfjww8/dIstT098++23mDZtmlXjXYVCgf/+978YP378c8+xatUqzJw502pyk0wmw/3791G1alW7xvy0PXv2YMyYMcjPz7f62KBBgyx6wria9u3b4+TJk1brnp6eiIuLK9EIduK6TCYTEhISkJ2djXbt2sHf37/YY7Ozs6FWq1GzZs1ybfvU6XRITEyERCJBRETEc7esVXT5+flYvXo19u3bB39/f0RFRaFr167PfExycjKWLVuGO3fuoGfPnpgyZUqZtu9xHIc5c+bgq6++KqpU8vLywm+//YZGjRqV6fkQQgghpGIpTTNr6lFEiIvLz8/H77//btW/RKPRYO3atW6VKMrIyLDZR0Oj0SAjI6NE5/j5559tjveWSqVITExEnz59yh1ncbp27WrVlwUwJ7pcfbKQTCazuc5xHKRSqZOjcR6DwQCtVguFQmGXXliFhYUQiUQulxQRCATo2LFjiY718fGBj49Pua8pkUie2T+psvHy8sLs2bMxe/bsEj8mLCwM27dvL/e1GYZBdHQ0oqKikJCQAD8/P3Tq1Mnlvk8JIYQQ4h6oRxEhLu5ZE2ueN+ra1XTs2NFmHw+xWGyzj4ct1atXt3nDbzQa7XLz+yxVq1bF8uXLIZfLi27APDw80LFjR7z++usOvXZ5TZw4EQqFwmq9atWqaNWqFQ8ROZZOp8O7774LLy8vVK1aFfXr10dcXFyxx+fm5uLbb7/Fl19+idOnT1s1Jr5w4QLCw8PBsixYlsWIESNsVpYRwqcaNWpg8ODB6Nq1KyWJCCGEEFJmtPWMEDfQpEkTXL161WJNLBZj7NixWL169TMfy3EccnJyIJfLLRrl8oHjOPTp0wfHjx+3qAoSCoWQSCTYs2cPevfuXezj1Wo1Vq5ciY8++siiskcgECAkJAQ3btxwygS1S5cu4bvvvkNubi4GDBiAPn36uPxNGcdxmDRpErZu3QqGYSAUCiEWi3HkyBGEhobyHZ7djRo1Crt27bKoYGNZFseOHcOLL75ocWxCQgL69OkDk8mEwsJCSKVS9OrVCz/88AOEQiH++usvNGnSBAUFBUWPkUqlePHFF3HixAmnPSfi/u7evYvs7Gw0adKkQlfyEUIIIcT1lGbrGSWKCHED586dQ7du3aDX64u20fj4+CApKQl+fn7FPi4hIQFjxozBnTt3AACvvfYa1q9fjypVqjgrdCt6vR6fffYZFixYYFW1wbIs7t+/b3OCz9GjR4smKul0uqIbepFIhKCgIPzyyy+oV6+eU56DO7t27RqOHz8OHx8f9O3bt0LerD569Ai1atWyqrhjGAb9+vXDzz//XLRmNBoRGBiIrKwsi2MVCgXWrl2Lt99+G++//z6WLVtmte2QZVkkJiaiRYsWjnsypELIzMzEm2++iaSkJEgkEnAchxUrVmD06NF8h0YIIYSQSqI0iSLaekaIG3jxxRdx/fp1fPDBBxg2bBiWLl2KK1euPDNJdPPmTfTq1Qvp6enQ6XTQ6XQ4cOAA+vbt68TIrYnFYuh0OpsVOAKBAAcOHLBaV6lU6NevHwoKClBQUGCxHW/jxo24du0aJYlKqFGjRhg/fjwGDBhQIZNEAHDv3j1IJBKrdY7jkJaWZrGWlJRkcwunSqXCxo0bAQCpqak2e1OJRCKkp6fbKWpSkfXr1w9nzpyBVqtFfn4+CgoKMHXqVJsN5gkhhBBC+EaJIkLcRPXq1TFv3jxs3bq12H4zT1uxYoVVfyOdToeUlBRcvnzZkaE+l0ajgdFotFrnOM7mTXtsbKzNLWUGgwFnzpxxynYz4j7q1atnM7EjFAqttp09q6rWZDIBAF566SWbzcD1ej2aNWtWzmjt4/r161i5ciU2bdqE3NxcvsNxSxzHYe3atQgODoZMJkN4eDiOHz9e7vNev34dly5dgl6vt1jXaDRYunRpuc9PCCGEEGJvlCgipIJKS0uzmpQGmKsgbt++7fyAnvLGG2/Y7JdkNBrRq1cvq3W1Wm3zht5oNEKpVDokRuK+vLy8EBUVZfU9JpfLMW/ePIu18PBwm9VHCoUCY8aMAfBPI3CB4J9/MuVyObp3716i0eN6vR6//vor9u3b55AkzsyZMxEaGopZs2bhP//5D2rWrInDhw/b/ToVUVpaGiZPnowePXqgT58+eO+993Dv3j0UFhYiOTkZvXv3xunTp8t1jYyMjGIr3P76669ynZsQQhwi7yZwaQ1w9nMgZSWQ/QffERFCnIwSRYRUUB06dLBZBaHT6XjvqdKxY0e8+eabRVVRAoEALMti/vz5qFmzptXxPXr0sJn0UigUGDBggMPjLYu8vDzExcXhzJkzz6xaeZ6CggKsWbMG77zzDtauXUuJsRL68ssvER0djeDgYCgUCnTr1g0nTpywSuyIRCLs2bMHHh4ekMvlEAgERcdHRkYCAPz8/HD27Fn069cPCoUCfn5+mDZtGn788cfnxnHu3DkEBQVh4MCBGDFiBAIDA7FmzRq7Pc+jR49i9erV0Gq10Gq1UCqVUKlUGDBggEUjb2ItLi4OYWFhWLduHX799VccOnTIosk+YE5S/zu5WFqhoaE2K9yeNE0nhBCXkncTuPY9oH4ImPSANhu4+TOQeYHvyAghTkTNrAmpoB49eoTGjRvj8ePHRdu8WJbFwIEDsXnzZp6jM7+afvToUezevRtSqRQjRox45pj2xYsXY/78+dBqtTCZTFAoFOjduzd27drlclvPVq1ahRkzZkAsFsNkMsHHxwfx8fFo2LBhqc5z+/ZtvPTSS1CpVFCpVFAoFPDw8MDZs2cRHBzsoOgrp+zsbPzwww/Izs5Gly5d0K5du3J/X+l0OgQGBiInJ8dinWVZnDx5Ei1btizX+QFg5MiR2LJli9W6p6cnvv/+e957krkqk8mEWrVq4f79+8891t/fHxkZGcV+/MGDB1i0aBHi4+MRGBiImTNnomfPnhbHLFq0CJ988klRIkoikcDX1xeXLl2Cj49P+Z4MIYTY06W1gPqB9brYA2g9HXCxv7kIISVXmmbWIkcHQwjhh6+vL5KTk/HBBx/gl19+gaenJ6ZMmYJp06bxHRoA8wSqrl27omvXriU6fubMmejSpQs2bdoEtVqNgQMHolevXi6XJDp9+jRmzpwJjUZTVNGhUqnQvXt3/Pnnnxbbl55n8uTJePToUVGvHJVKBY1Gg//85z/Yt2+fQ+KvrHx8fDB58mTk5+dj3bp1+OSTTxAcHIz//Oc/ZU7oHD582GYlnFarxYYNG7By5cryhm3V9+YJhmGK/RgxNzx//PhxiY59VoL34cOHCA0NRV5eHnQ6Ha5cuYLExERER0dj6tSpRcfNmjULTZs2xdKlS5GZmYm+fftixowZlCRyZ3o1YFAD0qqAwHo4AyFuS/vI9rpeDZh0gLBiDsIghFiiRBEhFVhwcDC2bt3Kdxh2Ex4ejvDwEiXBefPNN99YbfnhOA6PHz/G6dOn0bZtW6vHmEwmfPfdd/j6669RUFCAAQMGYPbs2YiPjy9KEj197KFDhxz6HCqrnJwctG7dGpmZmdBoNBAIBNi5cyc2b96MgQMHlvp8+fn5NrcdmkwmqyqjsoqMjMT+/fuhUqks1g0GA7p162aXa1REHh4eNhvq/xvLsvj000+L/fiiRYuQm5trkZRTq9V4//33MXbsWMjl8qL1vn37UoVXRWAsBG78BOSmA4zQXF1RuxfgX3xFLCFuReJl3m72b0IJIBA7Px5CCC+oRxEhhNhRVlaWzeQAwzDFVjC88847iIqKQkpKCm7evIkVK1YgPDwcQqHtV6lFIsrxO8LixYvx8OHDokSfyWSCWq3GhAkTylSd06VLF5uP8/DwsFtvrT59+hT1TgLMW5rkcjnWr18PT09Pu1yjIvLx8UGnTp0gFlve9IjFYsjlcjAMgzp16mDHjh3o0qVLseeJj4+3+TUWCAS4cuWK3eN2e5pHwON0oDCP70jKLn2POUnEGc3VFcZC4HYskHeL78gIsVaYBzw4Bfx9HFA9LNljanW1TggJxECNDgBDt46EVBb0004IIXZU3EQ3nU6Hdu3aWa3fuXMHW7ZssWiiq9PpkJmZidDQUKtpSRKJBEOGDLF/4AT79u1DYWGh1brBYMDVq1dLfb6AgAB8/PHHYFm2aIukQqHASy+9hP79+5c7XsCckNi+fTsOHTqEWbNm4eOPP8aVK1cwdOhQu5y/Itu+fTuaN28OhUIBLy8vSKVSjBs3DkqlElqtFrdu3Xru16lGjRo213U6HQICAhwRtnsyFgJXNpunKN3YbZ6idGOvOdniTnQF5ka//47bpAfuJ/ATEyHFybpk/lm7+xtw7yjwxwbgdgkqkn2aAiF9zT2JIACEMqBmZyDQuiKaEFJx0cvShBBiRyNHjsTq1auRnp4OtVoNhmEgl8uxYMECVKlSxer4s2fPQiwWQ6vVWqyr1Wr4+fmhUaNG+PPPP2E0GiEUClG/fn0sW7bMWU+nUqlatarNdb1eb/NrVxJz5sxBhw4dsH79euTn5+Ott97CwIEDS10VdvXqVUyfPh0nTpyAt7c3oqKiMH36dAiFQjAMg/bt26N9+/ZlirGy8vPzQ3JyMlJSUvDXX3+hVatWRYkfW+PsbZk5cyYSEhIsEr0SiQTt2rWzOcGx0vozFii4a06wGP/XtyvnCiD3M1cpuAu9yrzdzFaCqzDf+fEQUhyDBri1H+Ce6pNn0gOZyYBPE8DzOQMx/FsCfqHmxwhEVElESCVEiSJCCLEjmUyGxMREbNq0CXv37oWPjw+mTJmCDh1s3wwFBQXZ3KomFovRqFEjxMTE4NixY7h69SqaNm2Kjh07ulwD74ri3XffxcWLFy36/QiFQoSGhpZryly7du1sVpOV1J07d/Dyyy+joKAAHMdBqVTik08+wc2bN7F27doyn5eYtWzZsswNy1955RUsWbIEs2bNgkAgKKoc3LVrl52jdGMmA5CdaqMKxwA8POteiSK5DwBb04IFgFeIk4Mh5Bly083JnX9/u5r05kqj5yWKAHP/LWHJkuaEkIqHsXWDwpfw8HAuKSmJ7zAIIcRpOI5D48aNcePGDYvmuizL4uLFi6hfvz6P0VUuHMdh7ty5WL58OSQSCYxGI+rUqYO4uDgEBQXxFldUVBTWrFlj1QtHKpXizp07lXqLE8dx2L9/P7755hvk5+dj8ODBmDhxos3tn46k1Wpx9epV+Pn5USXRvxkLgXPRAEzWHxNIgIi5Tg+pXO4nAn8dMd9wAwAY8xSoFpMAadkqDwmxu0eXgVsHzH20/i3gRaAONdYnpDJiGCaZ47gSTQaiiiJCCOEBx3E4deoU4uPjMWTIEBw8eBCpqakQCoXw8vLCpk2bXDJJ9OTGfMuWLWAYBiNHjsSrr75aIaqcGIbBwoUL8d577+HcuXMIDAxEy5YteX9uZ86csdkwWSaTIS0trVInimbPno1Vq1YVVYFdunQJmzdvxpkzZyCVOm+Es0wmQ6tWNPXKJqHUXImjyfrXBxjAuy4vIT2TJsvc9FdaBfCoaa6qeFpQG0BW1dyTSKcEvEPM/VsoSURcSZX6AGcrOSsGfJs7Px5CiNuhiiJCCHEyk8mEoUOH4uDBg1Cr1ZBKpWAYBmvWrEGbNm1Qr149CASu2Q9gxIgR2Lt3b9GNuUKhwKBBg7Bx40aeI6u4xowZgy1btliNc5fJZLh27Vq5tsW5s7///hv169e36u+lUCjw9ddfY9SoUfwERqwV3AWubgVMRgAmc58fgRhoPh6Q+fAdnZnJCKT/COTdgHnWCwfIqgGNRwBiBd/REVJ6j1KBmz//7x2TeStaQARQuwevYRFC+FOaiiLXvBMhhJAK7KeffsLBgwehUqnAcRy0Wi00Gg2mTp2KWrVquWyS6Ny5c9izZ49FDx+VSoUffvgBFy5c4DGyim3GjBmQyWQWazKZDD169Ki0SSIAOHnypNV4e8D8PRkbG8tDRKRYnsHmrVkBYeZePoFtgNAprpMkAswVQrk3zL2TTDrz1jJNFnBzH9+REVI2vs2AVv8H1O5uHnnfbAIliQghJeaadyOEEFKBbdmyxSLZ8gTDMDhx4gQPEZVMfHy8VfUGYB4FHhcXx0NElUOTJk0QGxuLF154AUKhEDKZDCNGjMDOnTv5Do1Xvr6+NteFQiECAwOdHA15LpmPuS9Kk1FA8CuAxJPviCxlJltOiALMW3fybgBGG31eCHEHEk+g+ktAUHuA9ec7GkKIG6EeRYQQ4mRCobDYj7lqNREAeHl5QSKRWCWLJBIJvL29eYqqcujYsSOuXr0KtVoNiUQCkYj++e7UqRO8vLygVCotJgdKJBJMnDiRx8iIWzJZ9wEr8u+JbYQQQkgF57p3JIQQUkGNHj0aCoV1zwuGYdChg+uOih40aFCxiay33nrLydFUTizLOi1JlJiYiHHjxmHIkCHYs2ePVY8kvgmFQhw5cgT169eHQqGAl5cXPD09sWnTJjRp0oTv8Ii7qdIQgI3G9TJfQCR3ejiEEEIIn+glSUJIhaLX63H37l34+fnBy8uL73BsevXVVzF06FDs2LEDer0eEokEALB3796i/3dFAQEB2L17NwYPHmwxCWzXrl3FbgMi7unLL7/EggULoNFowHEcYmJi0LFjR8TExLhU1VvDhg1x7do1XL58GSqVCq1bt3botDOTyYQrV65AKpWiQYMGDrsO4UFwNyDvJmAsNFcXMULzW73+fEdGCCGEOB1NPSOEVBhr1qzBnDlzYDAYYDQaMXjwYKxZs8aqEbCruHjxIg4fPgxvb2+8+eabqFq1Kt8hlYhWq8Xvv/8OhmHQsWNHl/38krJ58OAB6tata7XF0MPDAzt27MBrr73GU2T8OnLkCCIjI6FSqWAymVC7dm389NNPaNSokdWxHMfhzJkz/8/encc3VeX/H3/dNGnStFDKvskOQmVTyiYKIoIg4i6KIi4jKLiMouL4VUdFcVecHy7jjiiKK4g74DIgiFJ2B1BZZd9L2yTN0tzfH8GONSlQmvam9P18PHhgzk3OfTMDbfPJOZ/D8uXLadmyJaeffnpCFdikBKEC2L0U8jZDSm2olwXJifmBg4iISGmV5tQzFYpE5JjwySefcOmll+L1eovGUlJSuOSSS3j99dctTCZSubz11luMHj2a/Pz8qGtXX301r732mgWprLVlyxaOP/74Yl9fDMOgbt26bN68udjpa16vl4EDB7JkyRJM0yQpKYmGDRsyd+5c6tZVM1kRERGxRmkKRfp4S0SOCQ899FCxN3EAPp+PadOmkZeXZ1EqkconLS2t2NbCPyQlJVXZpuWvv/56VI8m0zTxer18+eWXxcbvu+8+Fi1ahMfjwev1kpeXx7p16xg5cmRFRhYRERE5aioUicgxYcuWLTHHk5KS2Lt3bwWnEam8Bg4cGHObVHJyMldffbUFiay3ZcsW/H5/1HhhYSHbt28vNvbGG29EbdsLhUJ88cUXMecQERERSTQqFIlIuQmFQvzyyy/s3Lkz6lo4HOarr75iwoQJvPXWW/h8vjLd6+STT4755tbhcNCoUaMyzV1WBQUFvPvuuzzxxBN8++23JNKWX5G/crlcfP7552RkZFC9enWqV6+Oy+Xi6aefpmPHjlbHs0S/fv1IS0uLGjdNk1NOOaXYWCAQiDmHaZoJd3KciIiISCzqUSQi5eL9999n9OjRFBQUEAqFOPXUU5k2bRq1atXC4/Fw2mmnsWbNGrxeL263m5SUFL7//nvatGlzVPdbs2YNXbt2xev1Eg6HgchR4s8884ylWz7WrVtHr1698Hq9+Hw+XC4XHTt2ZM6cOaSk6MhlSVyBQICvv/4an89H3759K02z9fIQDAbp1q0bv/zyS1FROzU1lfPOO4+33nqr2HOvuuoqpk6dSigUKhozDIPu3bvzww8/VGhuERERkT+ombWIWCo7O5s+ffoU6xnkcDjo2rUr8+fP5+677+bpp58utj3DMAyysrL46aefjvq+a9as4b777mP+/Pk0adKEe+65h7POOqtMf5ay6t69O9nZ2UXFK4is2Bg3bhwPPPCAhclEpDS8Xi+TJk1i6tSpuFwuRo8ezZVXXhm1knHnzp107dqVffv24fF4cLvdJCcnM3/+fDIzMy1KLyIiIlWdCkVVQDAYZObMmSxZsoSWLVsydOjQmMviRaxw2WWXMW3atKgtVm63myVLltC/f382b94c9brk5GS2bdtGrVq1Kipqudq7dy8NGzaMuRWladOmbNy4seJDiUi583q9vP322yxatIh27doxYsQIatasGb8bFOyHrXMhbxMkp0OjUyG9RfzmP1qB3MgvV22wu6xOIyIiIn9SmkKRvbzDSPzt37+fnj17snXrVvLz80lNTeXOO+9kwYIFtG7d2up4ImzcuDFmHx6Hw8G2bdsO2aMnkYrXZfXnVUR/pV4lIscut9vNtddey7XXXhv/yQv2wcoXoTAAmJHH+Vug2VlQ98T43+9IFAZg7YeQsw5sSRAuhIYnQ+O+EFlePXIAACAASURBVOMEPREREUlsamZdCd19991s2LCB/Px8ADweD/v27eOqq66yNpjIQWeccQZOpzNq3O/306lTJ4YPH47LVfzTZsMw6NChA7Vr166omOWuTp06tGvXLuqocafTyWWXXWZRKhGp1LZ8978i0R/CQdj0FZgWFaDXfwI5a8EMQaE/8vv2H2D3MmvyiIiISJmoUFQJvf/++1FbWcLhMIsWLSoqHolY6eabb6ZGjRo4HI6isdTUVG677TZq1qzJ3XffTWZmJmlpaRiGQVpaGrVq1WLq1KkWpi4fU6dOpUaNGqSmpgKQlpbG8ccfzz333GNxMqmMDhw4wC233EK9evWoX78+t912G3l5eVbHkoqUu5FiRaI/mIXgP1DRaSJFq32rootU4SBsX1DxeURERKTMtPWsEvrr6oQjvSZSUWrXrs2yZcuYMGECn3/+ObVr12bs2LEMHToUiBRLFi1axFdffcWiRYto2rQpF198MW632+Lk8XfCCSewadMmpk2bxsaNG+nWrRuDBw/Gbj+2v/xu3bqVxx57jG+++YYmTZowbtw4TjvtNKtjVWqhUIhTTjmF3377Db/fD8Bzzz3HN998w+LFi6OaKkviycvLIxwOk56efvSTOKpF+gD9lRkGe5xPUty9HDZ/E7mfMwOanAG1/tKQu7AAKOFnj6AnvnlERESkQqiZdSU0duxYnn/++aI3CgBJSUn07t2bb775xsJkIiKwefNmOnfuTF5eHsFgEIj0bHnhhRcYMWKEZbk+//xzxo8fz6ZNm+jatSsPPfQQHTt2tCxPac2cOZPLL788auVoWloa77//PgMHDrQomRzO5s2bufLKK/n+++8BOPHEE5k8eTLt2rUr/WT7VsPajyIrdv5gJEFGW2hzcZwSA7uWwcbPit/H5oBWF0DNP+U2w7DkaQj+dUWzATUz45tJREREjlppmlnr48dKaPz48bRv3560tDTsdjvVqlWjfv36TJ482epoIiI89NBD5ObmFhWJIHIK1N///vdiYxVp8uTJXHzxxfz444/s2LGDTz/9lJNPPpnly5dbkudoLF26NOb2Yo/Hw6RJk9ixY4cFqeRwgsEgvXr1Yu7cuQSDQYLBIIsWLaJXr17k5sZYGXQ4NdtB49PBlhz5ZSRBjTbQ8tz4Bt/8dfEiEUQe/z6n+Jhhg2aDI0WkIjZISobjTo9vJhEREakQKhRVQmlpafz000989NFHPPzww7z++uusX7+eJk2aWB1N5Iht2bKFf//737z88svs2rXL6jjyJ6Zplun0udmzZxMKhaLGQ6EQ69atK0u0o1JYWMjtt9+O1+stGjNNE6/Xy//93//F5R55eXls3rz5kCfdlVXz5s1JS0uLGjdNk9mzZ9OyZUtmzZoVdd3r9XLXXXfRsGFD6taty4033sj+/fvLLacU9/nnn5OTk1PspEPTNAkEArz99ttHN2nDnpB1B7T/G5w0Fo6/JFKYiRczDMESel/5Y/zdqdUO2l0ZWdWUUhfqngQdR0NKrfhlEhERkQqjQlElZbPZ6N+/P3fccQcXXnghyclx/AFRpJz961//onXr1owdO5ZbbrmFpk2bHpONrCubvXv3MmzYMFwuFw6Hg8GDB/P777+Xep769evHHA8Gg5acardr165iRaI/mKbJTz/9VKa5PR4Pl156KXXq1OH444+nQYMGfPjhh2WasyQXXXQRKSkpMXsRBYNBvF4vl1xySbFVW6ZpcsYZZ/DMM8+wfft2du/ezcsvv0z37t2jDkWQ8rFhw4ZiW8X/4PF4ylY4tTnAXQ8cqWVIVwLDBo7ooiQAyTVij1drDMdfCp3GQIuzwVnC80RERCThqVAkIhXql19+4a677qKgoACfz4fX66WgoIBrr72WnTt3Wh2vygqHw5xyyil8+OGHBAIBCgsL+eqrr+jWrRseT+ka0t55551Fp7z9wel0MmDAAEsKRRkZGSVea9y4cZnmHjZsGDNmzMDv9+Pz+di1axcjRozghx9+KNO8sbjdbhYsWECPHj1KPLggHA6zcOHCosfz5s1j5cqVFBQUFI0FAgG2b9/O9OnT456xJDt37uTyyy8nLS2N6tWrc91113HggAUndFngxBNPjPlhTlpaGl26dLEg0RFq3Pcv28mIPNZ2MhERkWOeCkUiUqGmTZsWs0+NzWZjxowZFiQSiGwX27p1a7H/bwoLC/F4PLz77rulmuvcc8/l/vvvx+12U716dVwuF3379uWtt96Kd+wj4nK5uOaaa0hJKX4ilNvt5t577z3qebdt28bs2bOjVov4fD4ee+yxo573UFq1asX8+fPp27dvzOumaZKUlFT0eMmSJTH/veXn57No0aJyyfhXBQUFdOvWjffeew+Px0NeXh6TJ0+md+/e5bpVL1H07t2bDh064HK5isaSk5Np0KABF1xwgYXJDqNeF2g2KHLKGkByOjQfArXbRz83HIJ9a2D3MvDnVGxOERERibtj+3xmEUk4oVAo5ptD0zRj9rUpL0uXLmXJkiU0b96c0047rcofLb5mzZqYW5Hy8/P5+eefSz3f7bffzujRo1mzZg3169enUaNG8Yh51CZOnEg4HOb111/HZrORnJzMhAkTyvRGfcuWLSQnJxdbrQORv8vl3Yvp+uuv58cff4xa7eVyuejevXvR4+bNm5OcnBxVzHK73bRq1apcM/7hgw8+YN++fcX+fQcCAdauXcucOXMYMGBAheSwimEYzJkzhwcffJA33niDUCjEJZdcwvjx4xN/23jdkyK/TBNKWMWGZzusngLhQsCMPLd+N2jSv+TXiIiISEKr2u+MRCo5v9/P448/Trt27WjXrh2PPvpo1JvWRJOZmRmzUBQOhxkyZEi539/v93PmmWdyyimn8Pe//51zzz2Xdu3aVfltb5mZmTgcjqjx1NTUoz5CPjU1lS5dulheJAJwOBw8//zz7Nmzh1WrVrFr1y7GjBlTpjnbtWsXc7WOw+Ggd+/eZZr7cC688EIuuOACUlJSSE5OJjU1lWrVqjFjxoxiK4rOOussatSoUWzMMAxcLheXXXZZuWb8w/Lly2Oe1ub1ern88svLZZteonG73TzyyCNs27aNXbt2MWnSpENuiUw4JRV8zDCsmQohH4QDkVPRzBDsXAQH1lZsRhEREYkbFYpEKinTNBkwYAD3338/a9asYc2aNYwfP55+/fol9HaOxx9/POZ4ZmZmhZzc9/DDDzNv3jy8Xi8ej4f8/HzWr1/PVVddVe73TmT9+vWjWbNmxVY4JCUlkZ6eztChQ8vtvrt37+bBBx9k0KBB3HbbbWzYsKHc7gWR4lXTpk1jFsVKq1q1alH9mGw2G6mpqdx5551lnv9QbDYbU6ZMYcGCBTzyyCM8++yzbNmyhZNPPrnY8xwOB/Pnz+fUU0/F4XDgcDjo0qUL8+bNo3r16uWa8Q/t2rWL6ln1hz179jBgwAC2bt1aIVkkzvK3QGGMpujhIOxcXPF5pEgwGCQnJ6dMJ1gmpGB+ZIvjnhUQSuwPxkREKjMjkb6BZGVlmdnZ2VbHEKkUvv32W84555yoT+rT0tL48MMPE3I7R15eHjVr1oy5xSw9PZ2cnPLvbdGoUSO2bdsWNe5wONi/f3+Jb2irgv379zN27Fjee+89CgsLOfvss/nXv/5VbiuCNm3aRFZWFvn5+RQUFOBwOHA6ncyaNYuePXuWyz3jzTRN3n77bR5//HF27dpF3759eeihh2jRooXV0aLk5eURDodJT0+v0Pt6PB5atGjB7t27Y75pdTqd3HnnnTzwwAMVmkvi4MB6+OVdCEef6kb1FpA5ouIzVXGBQIDbbruNV199lVAoRP369Xn22Wc555xzrI5WdjuzYeOXkVP5ADCh1YVQs62lsUREKgvDMBabppl1JM/ViiKRSmrhwoX4fL6ocY/HU+zUo0TicDhK7AXkdrsrJMOhjgSPtY2orPbu3csjjzzCkCFDuOuuu9i8eXPc7xEvGRkZvP7663g8HgoKCvjggw/KddvYuHHj2LdvX9F2yWAwSH5+PiNHjiy3e8abYRhcfvnlLF++nO3bt/P2228nZJEIIiugKrpIBJFVXD/++CNt28Z+M+f3+1m7VtuUKqW0xkCMDxxtDqjdocLjCFx33XW8+uqr+Hw+gsEgmzdvZtiwYcyfP9/qaGXj2xMpEpmhg9scD251XPsBhLxlnz+QD+tnQvbjsGQibJ13sO+WiEjVpEKRSCXVsGHDqFOcIFJwSYSeMLG4XC4GDx4cte0nJSWlwooD5513XsxtR5mZmdSoUSOu99q4cSNt27Zl/PjxfPrppzz99NNkZmZS1VZOrl69mvvvv597772XpUuXFo3PmjUr5jbJX375hdzc3IqMKOWsWbNmh1zRkKjFNTmMpGRocQ7Y7BT9SGlzQGoDFYossH//ft55552oD5G8Xi8PPfSQRaniZM/KSE+sKEbkxL2yKPTDyhdh17JI0SlwALb+B357v2zziohUYioUiVRSF110UcyCh8PhKNeeMmX18ssvc8IJJ5CWlkZaWhopKSmcfvrp3H333RVy/wkTJtCgQYOiLWYul4vq1aszefLkuN/rjjvuKLZiJhAIkJ+fz6hRo+J+r0Q1ceJEunTpwoQJE3j44Yc55ZRTivr3lLTNz2az4XQ6KzKmVICNGzfGHDcMg6ZNm1ZsGImf2u2hw/XQoAfU6QytzofMKw8Wj6Qibd26tcST9H777bcKThNn4SAQo1BkmhAu44mpu5ZBYUHx+cOhSEN23+6yzS0iUknpu7hIJZWamsrcuXO5+OKL2bRpEwDHHXcc7733HtWqVbM4Xclq1arFkiVLWLhwIRs2bKBjx460b9++wu5ft25dVq1axdSpU/nhhx9o0aIFnTt3xuFwYJomRhyPc/7qq69irphZsWIFXq+3wrbblSQnJ4fp06fj8Xg488wzad26dVzn//333/m///u/Yifxeb1enn32WYYNG8aYMWN46KGHin36nZyczHnnnadC0THohBNOwOl04vcX72eTkpJSoV8DpByk1IamidcXr6pp3rx5zB6ANpuNbt26WZAojmq2i5ymF46xRTyjTdnmzvs99rzYwLMdUuqUbX4RkUpIhSKRSqx9+/asXr2aTZs2YZomTZs2jWuho7wYhkHPnj0ta1icmprKqFGjMAyDW265BbvdTigUokWLFnz22WdxO30tNTWVvLy8qPGkpKS4nLpVFrNmzeL888/HZrMRCoUYN24cN998M48++mjc7vHJJ5/E/PtYUFDAhx9+yH333cfKlSuZMWMGycnJhEIhTjzxRF566aW4ZZDSM02TefPm8c4775CUlMTw4cPp0aNHmecdNWoUTz75ZLFCUXJyMm3btqV79+5lnl+kqvvjxMUnnngCj8dTNO52u7n33nstTBYHaY2hdsfIaWd/FHVsDmh0KjjLuG08pRYYSWDG6ElU1rlFRCopbT0TOQY0bdqUZs2aVYoiUaL44YcfuOWWW/B6veTm5uL1elm9ejUDBw6M23HC1113XVQfqeTkZC644AJLC0Ver5cLL7wQr9dbdOKYz+fj2WefZe7cuXG7j91uj/l30mazYbfbsdvtvPPOO6xatYo333yThQsX8v3331vScFn+5+abb+ass87ixRdf5IUXXqBfv35x2Rpar1495s2bR9euXYuKpeeeey5z5szR1y6ROPnnP//JM888Q6tWrahevToDBgzg+++/p127dlZHKxvDgOZnQ9vLoV5XqN8DTrgaGvUu+9z1siKFomJs4EyHtOPKPr+ISCVkxOsNUTxkZWWZVa3Jq4hYY9iwYbz77rtRRaHU1FTmzZvHiSeeWOZ7BAIBLrnkEr766iscDgehUIhOnTrxxRdfWFoMmTlzJldccUVUw2jDMLj66qt59dVX43KfnTt30rx586jGqikpKSxZsqTEU7DEOkuWLOHUU0/F6y1+ilBKSgrLli2jTZsybvE4yOfzYbfbLV9ZJyICQP4WWDsD/Psjj6s3i/TbcqRZGktEJJ4Mw1hsmmbWkTxXW89EpErasWNHzJVDdrudPXv2xOUeycnJTJ8+nV9//ZWVK1fSsmVLOnfuHJe5yyJWDwuIbDkKBAJxu0+9evV46aWXGDlyJDabDdM0MU2Thx9+WEWiBPXJJ58U6yn1h3A4zGeffRa3QlGsExtFRCyT1hg63whBT6QRe5L65IlI1aZCkYhUSUOGDOHHH3+MWu3i9/vp2rVrXO/Vpk2buL3Bjod+/foRDEY37kxNTeWyyy6L672GDx9O//79+fjjjwmFQgwZMoTjjtNS/kSVkpKC3W6PKhgmJSWpuCMixz5H7NM4RUSqGvUoEpEqaeTIkTRq1KjYm9/U1FQefPBBatQ4tptXpqen8/LLL5OSkoLD4cAwDFJTUznvvPMYOHBg3O9Xr149Ro0axZgxY1QkSnCXXHIJNlv0jwamaXLBBRdYkEhEREREKpp6FIlIlZWbm8sLL7zA9OnTqVOnDjfffDP9+/e3OlaF2bBhA2+//TZ5eXmcffbZ9OrVS02FhSlTpnDdddcVNSMvLCzkzTffVKFIREREpBIrTY8iFYpERESqoE2bNrF+/XoyMzOpV69esWv79u3jyy+/xGazMWjQIJ1EJyIiIlLJqZm1iIiIxOT1ehk6dChff/01TqeTgoICRowYwQsvvEBSUuSI6Jo1a8a9X5WIiIiIVA7qUSSVwt69e7n22mupUaMGNWvW5IYbbog62ltERA7vpptu4uuvv6agoIADBw7g9/uZOnUqTz/9dMzn//E8EREREakatPVMEl4gEOCEE05g06ZNRSc1JScn07ZtW5YuXRqz8aqIiEQLBoNUq1YNv98fda1x48Zs3ry56HFOTg4jR45k5syZmKZJq1atePXVV+nZs+cR3y87O5vZs2eTnp7OxRdfTJ06deLy5xARERGR0inN1jO9w5aE9/HHH7Njx45ix3kHAgHWr1/P7NmzLUwmIlbZsmULW7dutTpGpRMIBCgsLIx5LScnp9jjQYMGMXPmTAKBAMFgkNWrV9O/f382bNhw2PuYpsmIESPo06cP//znP7n99ttp1qwZs2bNisufQ0RERETKjwpFkvCWLl1Kfn5+1HhBQQHLly+3IJGIWGX58uVkZmbSunVrWrVqRefOnVmzZo3VsSqN1NRUWrZsGTVuGAZ9+vQperxixQpWrFhBIBAo9jy/389zzz132PvMnDmTjz76CK/XSygUwufz4fV6ufjii2OuZhKRCmaGIeSL/C4iIvIXKhRJwmvTpg2pqalR4ykpKbRu3dqCRCJihQMHDtCnTx9Wr15NQUEBBQUFrFixglNPPRWfz2d1vErjpZdewu12FzWudjgcVKtWjSeffLLoOevXr8dujz7vIhQK8eWXXx72Hm+88QYejyfmtXnz5h1lchEpM9OErXMh+1FY/CQsfgJ2LLI6lYiIJBgViiThDR06lNTU1GK9iJKSksjIyODss8+2MJmIVKR3332XUChUbMw0Tfx+P9OnT7coVeXTu3dvsrOzueqqq+jRowc33HADP//8M23bti16TseOHaNWE/3h119/5bvvvjvkPQ7V/zCReiOKVDnbvoet86AwAGZhZFXR77Ng9wqrk4mISAJRoUgSntvtZuHChfTp04ekpCTsdjv9+/dnwYIFOBwOq+OJSAXZvHlzzFUqPp+PLVu2WJCo8mrXrh2vvPIKP/zwAxMnTuS4444rdr1Fixb069cv5muDwSBPPfXUIee/8sorY64EhUihSkQsYJqwbT6Eg8XHw0HY+p0lkUREJDGpUCSVQvPmzfnmm2/Iz88nPz+fL774gkaNGlkdS0QqUPfu3UlLS4sadzqddO/e3YJEx7Zx48bhdDpjXtu+ffshX3vuuedywQUXFG1xS0lJwe12895775U4p4iUMzMEhSX0CAvkVmwWERFJaNENCEQSmMvlsjqCiFhk0KBBtG3blp9//pmCggIg0qssKytLq1TKQZcuXYr6GP2Z0+lk0KBBh3ytYRhMmTKFm266idmzZ5Oens7QoUOpU6dOecWtcH6/nw8++IC5c+fSrFkzrr76aurXr291LJGSGXZwpEEwL/payrHzb1NERMrOSKReAVlZWWZ2drbVMUREJEF5PB6eeuoppkyZgs1m4+qrr2bs2LFapVJOJk2axD/+8Q+8Xi8QKRLVrl2b5cuXU6tWLYvTWSc3N5cePXqwefNm8vPzcblc2O12Zs2aRc+ePa2OJ1KyPStg/SfFt5/Z7HD8ZZDewrpcIiJS7gzDWGyaZtYRPVeFIhERESnJnDlzeOqpp9ixYwdnnXUWt956K7Vr17Y6lqXuuusuJk6ciN9ffBtP8+bNWbduHYZhWJRM5AjsWwNbvgV/DqTUhuPOgPTmVqeqekI+2LUEDmyAlFpQr1vkdxGRcqJCkYiIHNtME3y7wQyDuy4YarknFadly5asX78+ajwlJYVVq1bRrFmzig8lIpVHIB9WvgiFPgiHABvYkuD4YVrZJSLlpjSFIvUoEhGRUtmyZQvffvstGRkZDBgwgOTk5IoN4NkOv0yDkBcwICkZ2gyFak0qNodUWSVtdTRNU9sgReTwtnwHQQ8QPjgQhnAY1s2AE28FrUoUEYvpI1gRqZKWLl3KiBEj6N27N+PHj2fv3r1WR0pYCxYs4JRTTiE9PZ06derQokULxowZw2WXXUbDhg1ZunRpxYUpDMCqNyBwINJjIxyAYD6sfguC3orLIVXaddddh9vtLjZms9no0KEDDRo0sCiViFQaOb/yvyLRn4S8ke9vIiIW04oiEalyPvroI6644goKCgoIh8MsWrSIF154gaVLl+rUor/44Ycf6N+/f1Ez4z8Eg/9rhHrWWWexZcuWmCdkxd2+1ZHtZn9lhmHvSqjfvfwzSJV3ww038N133zFr1iwAkpKSSE9P591337U4mYhUCkklrMQ1zZKviYhUoDKtKDIM42LDMP5rGEbYMIysv1y7yzCMtYZh/GIYxplliykiFW3WrFn06dOHpk2bMmzYMNasWWN1pLgoLCzkuuuuw+v1Eg5HCg4FBQXs3buXhx9+2OJ0ieeuu+6KKhL9lcfjYeHChRUTKJgPZih63AxBIMaRzyLlwG63M336dBYsWMDEiROZNm0aGzZsoHlzNQQWkSNQrzvYHH8ZtEH1pmB3x3yJiEhFKuuKop+BC4AX/zxoGEYmcClwAtAQmGMYRhvTNAvLeD8RqQBTpkxh9OjRRQWCLVu28Omnn/Ljjz+SmZlpcbqyWbduHT6fL2o8GAzy6aef8v/+3/+zIFXiWrFixWGfYxjGYYtJcVO9KRhJ0auKbMlQvVnFZBA5qFOnTnTq1MnqGCJS2dTrEum3t2dFpIm1GQZXLWh1odXJRESAMq4oMk1ztWmav8S4dC4wzTRNv2maG4C1QLey3EtEKkZhYSFjx44t9sY/HA7j8Xi45557LEwWH+np6YRCMVakALVq6Vjav2rS5PANokOhEL169aqANEBqo8iJMH/+JNbmgLQGkN6CtWvXMmbMGHr16sWtt97K77//XjG5REREDmf/r7D6Tfj5FXBlQIdR0PI8yLwaOlwHjlSrE4qIAOXXo6gR8Od9CFsOjolIgtu+fXvM1SGmaTJ//nwLEsVXvXr1OOWUU5g7d26xPjupqamMHTvWwmSJ6YEHHuCyyy6L+XfCbrfjcDh46aWXohr7lhvDiJxwtmsZ7FoChKF2Z6jXhR9/WkS/fv3w+/2EQiEWLVrEa6+9xoIFCzjhhBMqJp+IiEgsm7+F7QsiBzEAeHfB7mWRApH6EolIgjlsocgwjDlArO6ud5um+XFJL4sxZpYw/yhgFBzZJ9ciUr4yMjIwzZj/XGnYsGEFpykf06ZN4+yzz2blypU4HA78fj833XQTl156aYVn+fXXX/n0009xOBxceOGFCfe/8bnnnsvzzz/PuHHjyMnJweFwMHDgQNxuN3Xr1uVvf/sb7dq1q9hQRlJk2X69LsWGR48ejcfjKXocDAYJhULccsstzJ49u2IzioiI/CHogW3fw5+7cJghCORGikX1tfFCRBKLUdIbwlJNYhjfAbebppl98PFdAKZpPnLw8VfA/aZp/nCoebKysszs7Owy5xGRsvnb3/7GO++8U6yXj9vtZsqUKVx44bGzf3716tVs3bqVzp07U7t27TLNtWLFCtauXUvHjh1p1arVEb3mgQce4LHHHqOwsJCkpCRM0+Tll19m+PDhZcpSHsLhMLm5uaSlpWG3J96BmcFgEKfTGbPI6XQ6KSgosCCViIgIsP8XWPsRFPqjr6W3gnaJ931fRI49hmEsNk0z6/DPLL+tZzOBtw3DeJpIM+vWwE/ldC8RibPnn3+ewsJCpk2bhsPhwDAMHnzwwWOqSATQrl27Mq+Gyc3N5ayzzmLp0qXY7XaCwSCDBg0q+t+uJEuWLOHxxx+Paqw9cuRIBg4cWObCVbzZbDZq1KhhdYwS2e12XC5XzEbl1atXtyCRiIjIQXY3xPxw3oDkahUeR0TkcMrUzNowjPMNw9gC9AQ+O7hyCNM0/wu8B6wCvgRu0IlnIpWH0+lk8uTJ7Ny5k8WLF7N7927+/ve/Wx0rIY0ZM4bs7Gy8Xi+5ubn4fD6++OILJkyYcMjXTZs2LeYqF7vdzieffFJecY9ZhmFwzTXX4HK5io2npKRwww03WJRKREQESGsMjjSiunPY7KXbdrZvFSybBD8+GPl935q4xhQR+UNZTz2bbppmY9M0naZp1jNN88w/XZtgmmZL0zSPN03zi7JHFZGKlp6eTps2bXA6nVZHSUjBYJD3338fv7/4UnKfz8e///3vQ77WNM2Y26RKGq9oXq+XO+64gzp16lCjRg2uuuoqdu7caXWsQ3ryyScZMGAALpeL9PR0nE4nF154IXfffbfV0UREpCozDGh3BaTUjpzUmeQEWzI0PxtSbeQBlQAAIABJREFUGxzZHHt+jmxfK9gb6XVUsBfWfgB7V5VvdhGpkuLSoyhe1KNIRCoTn89HtWrVKCyMXjCZlpZGXl5eia9dtGgRp512WtRpYi6Xi02bNlG3bt245z1Spmly6qmnsnjx4qJVT3a7nQYNGrBmzZqKO+HsKG3cuJG1a9fSrl07GjXSgZsiIpJAfLshVACp9SNFoyO1ZCIEDkSPO2vCiTfHL5+IHLNK06OoTCuKRESqspSUFDp06BA1brPZGDBgwCFf27VrV2688UZSUlKw2+0kJyfjcrmYNGmSpUUigIULF7Js2bJiW+NCoRD79u1j2rRpFiY7Ms2aNeOMM85QkUhERBJPSh2odlzpikSmGbtIBODfH59cIiJ/knhH14iIVCIvv/wyffv2JRAIEAgEcLlcpKam8uSTTx72tY899hjDhw9n5syZJCcnc/HFF9OsWbPyD30Yy5cvJxwOR417PB4WLVrENddcY0EqERGpMIE8+H0O7F8DRhLU6QzH9S1dcUPixzDAUQ2CMVYqJ+vABhGJPxWKRETKICsri1WrVvHcc8+xcuVKevbsyfXXX3/Ep5Z16NAh5qokK7Vs2RK7Pfrbg9vtpm3bthYkEhGRClMYgJ9fhkA+cPBDgx0/Qv5WyLwqUrSQitf4NNj0JYSD/xuzOSIFPBGROFOPIhERKSYcDtOuXTs2bNhAMBj5gdQwDGrUqMG6devIyMiwOKGIiJSbXYth418KEhApSrS7Eqo1tiaXwM5s2PItBD2RU9SOOx3qnmR1KhGpJErTo0grikREpBibzca8efO49tpr+fLLLzFNk6ysLF577TUViSq5lStXsmHDBjp27JgQ2xxFJAHlb40uEgGYgHeHCkVWqpcFdbtETj2zJeDbON+eSDErcADSW0LtjpCUbHUqETkKCfgVRkRErFa3bl1mzpyJ3++nsLAw4U86k0PLyclh8ODBLFu2DLvdTiAQ4IILLuCNN96Iuc1QRKow18Ej3P9aLDIMcNW0JpP8j2GAkYBft/f/Ar+9D+EwEIactbD9B2g/Euwuq9OJSCnp1DMRESmR0+lUkegYMHLkSLKzs/F6veTm5lJQUMCMGTN4+umnrY4mIommbudIA+tibJBcDao3syKRJDqzENbNgHCIor5W4SD4D8COhZZGE5Gjo0KRiIjIMczn8zFz5kwCgUCxca/Xy7PPPmtRKhFJWHY3nHANpDUCbGDYoEYrOOHqyH+L/JV3N4QLo8fNEOxdVfF5RKTMEnDdooiIyLHnwIEDTJo0iY8//pjatWvz97//nYEDB5b7ff1+PyUdXJGfn3/U8y5atIinnnqK9evX07dvX2699Vbq169/1POJSAJx141sGSoMRIpDidgPRxJHUjJFK4liXhORykZf9UVERMpZbm4uJ510Etu2baOgoACAefPmcc899/CPf/yjXO9do0YNWrZsyZo1a4qN22y2oy5UffTRR1xxxRX4fD5M02TFihW89tprLF26lMaNS250Gw6H2bVrF+np6aSkpBzVvUWkAulNvhwJV01w1QLvLiJdzw+yOaB+d8tiicjR0/pRERGRcvbSSy+xffv2oiIRgMfj4YEHHiAnJ6fc7//KK6+QmpqKw+EAwOVyUbNmTR599NFSz1VYWMj111+P1+stWqnk9/vJyclh/PjxJb5u6tSp1K9fn+bNm1OzZk1Gjx4dtR1OREQqqTaXgjMdbMmRX4Yd6pwItdpbnUxEjoJWFImIiJSzTz/9FJ/PFzXudDpZtGgR/fv3L9f79+rVixUrVjBp0iRWr15Nr169GD16NLVr1y71XJs2bcLj8USNh0Ihvvzyy5ivmT17NqNGjcLr9RaNvfHGGwQCAV599dVSZxARkQTjyoDON0Pe7xDIh2qNwVnD6lQicpRUKBKRUsnJyWHGjBnk5+dz5pln0rp1a6sjiSS8hg0bYhhGVK+gUChEnTp1KiRDixYtmDhxYpnnqVGjBoWFMZqWQomFpwcffLBYkQgiTbbffvttJk6cSPXq1cucS0RELGbYdDKeyDFCW89E5IjNnj2bRo0acdNNNzFu3Dg6duzInXfeaXUskYR38803R/XkSUpKolmzZnTq1MmiVEenZs2a9O/fn+Tk4r1LUlNTuf3222O+ZuPGjTHH7XY7O3fujHdEERERESkDFYpE5Ij4fD4uvPBCvF4v+fn5+Hw+CgoKePbZZ/nPf/5jdTyRhNajRw8mTZpEWloa1atXx+120759e7788ksMw7A6Xqm9+eab9OrVi5SUFNLT03G5XNxyyy0MGzYs5vO7d++OzRb9I4dhGDRp0qS841Yo0zSZP38+zzzzDNOnTycYDFodSURERKRUtPVMRI7I119/HfMNrc/nY/LkyfTp08eCVCKVxzXXXMOwYcNYtmwZGRkZtG3b1upIR61GjRp88803rFu3jq1bt9KhQwcyMjJKfP4DDzzAl19+icfjKdp+53a7eeCBB3A6nRUVu9wVFBQwcOBAsrOzCYVCJCcnU61aNb7//nuaN29udTwRERGRI6IVRSJyREr6VNw0TZ1cJHKEUlJS6NmzZ6UuEv1Zy5Yt6d279yGLRACZmZksWLCAwYMHU7t2bTp06MDrr7/OrbfeWkFJK8YTTzzBTz/9hMfjwe/3k5eXx44dO7jsssusjiYiIiJyxIy/Nta0UlZWlpmdnW11DBGJITc3l/r160ed3JSamsq7777L4MGDLUomIpIYmjVrxqZNm6LGk5OT2bZtG7Vq1bIglYiIiAgYhrHYNM2sI3muVhSJyBGpXr06L7/8MikpKUVNbFNTUznnnHM466yzLE4nImK9kk6DMwyDUChUwWlEREREjo4KRSJyxC6//HL++9//cu+993LHHXfwxRdfMHXq1ErZjFdEJN4uvfTSmD2XWrduTd26dfnXv/5FgwYNsNvtdOrUiW+++aZU869Zs4ZZs2bppDgREREpV9p6JiIiIhIHubm59OzZk99//538/HzcbjcOh4O5c+cyffp0Hn/8cbxeb9Hz3W43s2fP5uSTTz7kvPv372fIkCEsWbKE5ORkCgoKGDVqFP/6179UqBcREZEjUpqtZyoUiYiIiMRJMBhkxowZ/PDDD7Ro0YLhw4fjcrmoXbs2Ho8n6vn9+vVjzpw5h5zznHPO4auvvip2cIDb7eaZZ55h5MiRcf8ziIiIyLFHhSIRERGRBLFp0yYyMzOLrSb6Q/369dm+fXuJrz1w4AB169aNebpkZmYm//3vf+OaVURERI5NpSkU2cs7jIiIVC0+n4///Oc/GIZBnz59cLlcVkcSsVS9evVKvJaZmXnI1+bl5ZGUlBTz2v79+8uUS0RiMMOQ8xvkbQFnOtRqD3Z9HxORqkXNrEVEJG4+++wz6tWrxyWXXMLQoUOpV68es2bNsjqWiKVcLhe33norbre72Ljb7eb+++8/5GsbNWpEzZo1o8btdjuDBg2KZ0wRKQzAzy/Dbx/Ctnmw6StYOhE8O6xOJiJSoVQoEhGRuNixYwdDhw4lLy+P3Nzcol/nn38+e/futTqeiKXGjx/PfffdR+3atTEMg7Zt2/LRRx9x6qmnHvJ1hmHwyiuv4Ha7i1YWuVwuMjIyeOCBByoiukjVse178O6C8MGtnuEgFPph7QfW5pKS5f0O6z+BdR/DgXWQQG1VRCozbT0TEZG4eO+99wiHwzGvvf/++1x//fUVnEikdDZu3Mgbb7zBrl27GDRoEIMGDSpx21dp2Ww2xo0bx7hx4zBNs1SnlQ0cOJAff/yRZ555ht9++43TTjuNG2+8kTp16sQlm4gctGclmIXR4wU54D8Q2YomieP3r2HHwkhBD2Dvz1DrBGhxLuhESJEyUaFIRETi4sCBAzEb7gYCAQ4cOGBBIpEj98knn3DJJZdQWFhIIBBgypQpdO3ala+++gqHwxHXex3Nkfbt27fnlVdeiWsOEfmrkv5tmio8JJqCvbD9BzBD/xsLB2Hvf6FuF6h2nHXZRI4B2nomIiJxMWDAgJiNq5OTkznzzDMtSCRyZPx+P8OHD8fn8xUVO/Pz8/npp5946623LE4nIhWmTmcwYnyOnlIbkqtXfB4pWc7a2OPhIOz/pWKziByDVCgSEZG46NatGxdccAGpqalFY6mpqQwbNozOnTtbmEzk0H788ceY4x6PhzfffLOC04iIZRqeDGmNwJYM2CK/293Q+mKrk8lf2RyxV3kZtsg1ESkTbT0TEZG4MAyDKVOmMHPmTKZMmYLNZuPKK69k8ODBVkcTOaTk5GTMEhqgxlold6R8Ph9vvfUWn376KQ0aNGD06NF06tTpqOcTkXJms0PmVZC3CfK3RlYR1WyrwkMiqtkWNn4ePW7YoHaHis8jcowxSvrByApZWVlmdna21TFEpBLJzc1l8uTJfPfdd7Rp04brr7+eZs2aWR1LRCqRcDhM48aN2b59e7Hx1NRU3nrrLc4777xSz+nxeOjRowfr16/H6/WSlJSE0+nkpZde4vLLL49XdBGRqmv/r/Db+xT1ljLD0OLsyBZCEYliGMZi0zSzjui5KhSJSGW1a9cuTjrpJPbv34/X6yU5ORmHw8EXX3xx2COnRUT+bPHixZxxxhkUFhZSWFhIOBzm6quv5rnnnjuq5tNPPfUU9957Lz6fr9h4tWrV2LVrV5lWKomIyEGFfshZFykS1WgJ9hSrE4kkrNIUirT1TEQqrfvuu49du3YRDEaORQ0EAgQCAa666irWrl17VG/uqjrTNFmwYAGbNm2iS5cuHH/88VZHKsbn8/HJJ5+wa9cu+vTpQ4cOWl4u8dGlSxe2bdvGZ599xt69e+nbty9t2rQ56vk++OCDqCIRRLZoLl68mF69epUlroiIACQ5oVam1SlEjjkqFIlIpTVz5syiItGfbdu2je3bt9OwYUMLUlVeO3fu5PTTT+f333/HMAyCwSBnn30277zzDna79d8uli9fTt++fQmFQgSDQQzD4Pzzz+fNN9/EZtPZDFJ2KSkpXHTRRXGZq0aNGjHHCwsLqV5dpyeJiIhI4tJP1iJSaf35dK0/C4fDpKRo6XFpXXHFFfz666/k5+eTl5dHQUEBn3/+Oc8884zV0TBNk/POO4/9+/cXZfP5fHz88cdMnTrV6ngiUW688caor1GGYdCoUSPat29vUSoRERGRw1OhSEQqrTFjxuB2u4uN2e12+vTpQ0ZGhkWpKqecnBz+85//EAqFio17vV5eeOEFi1L9z88//8zu3bujxj0eDy+99JIFiUQObfDgwYwdOxaXy0X16tWpVq0aTZo04bPPPtO2WKm6gvmw8QtY+gys+DfsXgYJ1C9VREQirN9LICJylG666SYWLVrERx99hMPhwDRNmjVrxltvvWV1tErH7/eX+ObV6/VWcJpowWCwxO1lfr+/gtOIHJnx48dzww03sGDBAmrXrk2vXr20TVKqrpAPVrwIIU+k8TDAhs/AswOaDbQ2m4iIFKNCkYhUWklJSUydOpW1a9eyePFimjZtSvfu3fVp/VGoW7cuTZo04bfffis27nA4jupo8Hjr1KkTLpeLvLy8YuNut5sRI0ZYlErk8OrVq8f5559vdQyR+AnkwuZvIWct2F1QvwfUPQkO9713Z3akWPRHkQggHISdi6BhL0iuVr65RUTkiBlmAi33zMrKMrOzs62OISJSJS1YsIAzzzyz6PQ4t9tNzZo1Wbx4MXXr1rU6Ht988w1DhgyhsLAQv99PWloanTt3Zs6cOTidTqvjiYgc+4IeWP5cpODDwfcQNkekUNRs0KFfu+oNyN0QPZ7khFYXQsbRnzIoIiKHZxjGYtM0s47kuVpRJCIiAJx88smsWrWKF198kV9//ZXevXtz5ZVXUq1aYnzKe/rpp7N27VrefPNNtm3bRr9+/TjrrLNISkqyOlqlsmzZMmbPnk16ejoXXXQRNWvWtDqSiFQWO36CQj9FRSI4uCpoMTQ8FZLTSn6tKwNyNxZ/LURWGCXrJEARkUSiFUUiIiJVgGmajBw5knfeeYdgMIjD4QDg448/5owzzrA4nbVyc3NZuHAh6enpdOvWTdtXRUry39chb1P0eJITWl8MNVqV/FrvTvj5lUhhqYgN3HWh4/VxjyoiIsWVZkWROiqKiIhUAZ9++inTpk3D6/USDAbxer14vV4uuuiiKt0Q/Pnnn6d+/fpcfPHFnHHGGTRv3pxffvnF6lgiiclVE4hRSDXD4Ew/9Gvd9aD1RWBPjWxXM5KgehNoN7xcooqIyNHT1jMREZEqYPLkyXg8nqhx0zSZO3cu/fv3tyCVtRYuXMgdd9yBz+fD5/MB4PF4GDBgABs2bNAJZSJ/1aAH7P25+KogwxYpAqXUOfzrM46HLrdBwf7IKqRDbVUTERHL6CcgEREpV/v27WPPnj1Wx6jywuFwidcSaRt6RXr++eeLCkR/ME2Tffv2sXDhQotSiSQwdz1oPRQc1cBmj6wKSm8JbS8/8jkMG6TUUpFIRCSBqVAkIiLlYt26dfTo0YMGDRrQqFEjTjrpJFatWmV1rCprxIgRpKamRo2bpknv3r0tSGS93bt3xyyS2Ww29u/fb0EikUogozWcdCt0uhG63B4pEtlTrE4lIiJxpEKRiIjEnd/vp1evXixatIhAIEAgEGDZsmWccsop5OXlWR2vSjr33HM555xzSE1NxTAMXC4Xbrebd955B5fLZXU8S5x//vm43e6o8UAgwMknn2xBIpFKwrCBs4YKRCIixygVikREJO4+/vhjvF5vse1OpmkSCAR49913LUxWddlsNqZOncqcOXO47777ePTRR1m3bh2DBw+2OpplRowYQZs2bYqKRYZh4Ha7mTBhAhkZGRanExEREbGGmlmLiEjcbdq0Kar3C0QaBW/YsMGCRAKRQkiPHj3o0aOH1VESgsvlYsGCBbzxxht8+OGH1KpVizFjxlTZrXgiIiIioEKRiIiUg6ysLFwuF/n5+cXG09LS6Natm0WpRKKlpKRw/fXXc/3111sdRURERCQhaOuZiIjE3WmnnUaHDh2K9b5xOp00b968Sm91EhERERFJdCoUiYhI3BmGwddff80dd9xBkyZNaNSoETfffDPz58/HbrdmMWswGOTuu+8mIyMDh8NB7969WbZsmSVZREREREQSlRHrWFirZGVlmdnZ2VbHEBGRY9Dll1/O9OnTi/VOSktLY/ny5bRo0cLCZCIiIiIi5cswjMWmaWYdyXO1okhERI55W7du5aOPPopqsO33+3nqqacsSiUiIiIiknhUKBIRkWPer7/+itPpjBoPBoMsWbLEgkQiIiIiIolJhSIRETnmtWrVCr/fHzVut9vp3LmzBYlERERERBKTCkUiInLMO+644xgyZAgpKSnFxp1OJ7fddptFqY5t4XCYTZs2kZOTY3UUERERESkFFYpERKRKePPNNxkzZgxpaWkYhkG3bt349ttvadWqldXRjjnTp0+nYcOGZGZmUr9+fc4//3wOHDhgdSwREREROQI69UxERIoJh8O8++67vPTSSwQCAYYPH87f/vY3kpOTrY4WN6ZpYhiG1TGOSdnZ2fTp0wev11s05nQ6OfXUU5k9e7aFyURERESqLp16JiJSRU2dOpXWrVvjdrvp0qULX3/9dannuPrqqxk5ciTfffcdCxYs4Pbbb+eMM86gsLCwHBJbQ0Wi8vPEE0/EPF3u+++/Z+PGjdaEEhEREZEjpkKRiMgx4sUXX2TUqFGsXbsWn8/HkiVLGDJkCN9+++0Rz/Hf//6X999/H4/HUzTm9XpZunQpX3zxRXnElmPMunXriLVa2el0smXLFgsSiYiIiEhpqFAkInIMCIfD3HPPPcW2+wD4fD7+8Y9/HPE83333Xczx/Px8bRuSI9K3b9+Y2xT9fj8nnHCCBYlERCoZ7y7Y+zN4dlidRESqKLvVAUREpOxyc3PJzc2NeW316tVHPE+dOnWw26O/NTidTurXr3/U+aTqGDt2LK+//jo5OTlF2xXdbje33HILGRkZFqcTEUlg4SD88i7kbSTyeb4JqQ2g7eWQ5LQ4nIhUJVpRJCJyDKhWrRoulyvmtWbNmh3xPEOGDIlZKEpKSmLEiBFHG0+qkAYNGrBkyRKuuOIKGjVqRKdOnXjxxRd56KGHrI4mIpLYNn8LuRshHIJwIFI4yt8KGz63OpmIVDEqFImIHAOSkpK48847cbvdxcbdbjcPPvjgEc+TkpLC119/zXHHHUdaWhrVqlWjZs2aTJ8+nUaNGsU7thyjmjRpwuuvv86WLVtYtmwZw4cPVwNxEZHD2bUUzFDxMbMwsg3NDFuTSUSqJG09ExE5Rtx1113Y7XYeeeQR8vLyqFevHo8//jjnnntuqeY58cQT2bRpE8uWLSMYDHLSSSfFXGUkIiIicRQOxh43w0D0IQEiIuXFiHUyiVWysrLM7Oxsq2OIiFRqpmni9/txOp1axSEiIlJZrHkbcn4jqiiU1hjaX2tJJBE5dhiGsdg0zawjea62nomIHGMMw8DlcqlIJCIiUpk0Gwh2FxgHV/EaSZEm1s3PtjaXiFQ52ksgInIUNm/ezK+//krr1q1p0qSJ1XFERESksnPVhE43ws7F4NkK7npQryskV7M6mYhUMSoUiYiUQiAQYMSIEXz88cc4nU78fj+DBw9m6tSpOJ06ulZERETKwJEKjXtbnUJEqjhtPRMRKYX77ruPmTNnUlBQwIEDBygoKODzzz/n7rvvtjqaiIiIiIhImamZtYhIKWRkZJCTkxM1npaWRl5engWJREREREREDk3NrEVEykl+fn7McY/HQyIV3kVERERERI6GCkUiIqXQs2fPmOPdunXTKWMiIiIiIlLpqVAkIlIKkyZNIi0tDYfDAYDdbictLY3nnnvO4mQiIiIiIiJlp1PPRERKoVOnTqxYsYKnn36aJUuW0LlzZ8aOHUvLli2tjiYiIiIiIlJmamYtIiIiIiIiInIMUzNrEREREREREREptTIVigzDeMIwjDWGYawwDGO6YRg1/nTtLsMw1hqG8YthGGeWPaqIiIhUtL179/LPf/6TrKwszjnnHL777jurI4mIiIhIOSrT1jPDMAYA35imGTIM4zEA0zTvNAwjE3gH6AY0BOYAbUzTLDzUfNp6JiIikjj27NlD586d2bNnD36/HwC3283TTz/NddddZ3E6ERERETlSFbb1zDTNWaZphg4+XAg0Pvjf5wLTTNP0m6a5AVhLpGgkIiIilcTEiROLFYkAvF4vt99+Oz6fz8JkIiIiIlJe4tmj6Brgi4P/3QjY/KdrWw6OiSScn376iZNPPhmHw0HdunWZMGEChYWHXPwmIlIlfPbZZ8WKRH+w2WysXLnSgkQiIiIiUt7sh3uCYRhzgPoxLt1tmubHB59zNxACpv7xshjPj7nHzTCMUcAogCZNmhxBZJH4WbVqFaeffjoejweA3bt38/DDD7Nt2zaee+45i9OJiFirfv36LF++PGo8GAxSp04dCxKJiIiISHk77Ioi0zTPME2zfYxffxSJrgTOBi43/9fwaAtw3J+maQxsK2H+l0zTzDJNM0s/dEpFe+SRR6K2T3i9Xl577TX27dtnUSoRkcQwduxY3G53sTG73U7nzp1p3ry5RalEREREpDyV9dSzgcCdwDmmaXr/dGkmcKlhGE7DMJoDrYGfynIvkfKwZMkSwuFw1HhycjLr16+3IJGISOIYMGAAEyZMwO12U716dVJSUujSpQszZsz4/+3db6ye9VkH8O/VUhgwCE5AxlplS9BQRztJw5/ICzKWDJWAM8wMZgQ1miUzrIlGByQaNXthFmTRoWLsIiboaJxzZDIZzpmZkG4eXEE29qdqtqlNEaSC1HbtzuWL5+56AidrOX3Oc3NOP5/kpM/9u++eXC++PU+f77n/jD0aAADL5HjvUfTBJGckebiqdlbVHyZJd38hyfYkX0zyN0nefbQnnsEYLr744qxZ89J/BgcOHMgFF1ww+4EAXmG2bt2aPXv25MEHH8xjjz2WHTt25Nxzzx17LAAAlkkduVpsfFu2bOm5ubmxx+AE8vjjj+eKK67Ivn1HTog79dRTc+ONN2bbtm0jTgYAAADTUVWPdveWYzl2mk89gxVn06ZNeeihh7J58+YkyZlnnpmtW7fmnnvuGXkyAAAAmL2jPvUMVrsrr7wyO3fuzPz8/KKXoQEAAMCJwqdiGCiJAAAAONH5ZAwAAABAEkURAAAAAANFEQAAAABJFEUAAAAADBRFAAAAACRRFAEAAAAwUBQBAADHp+eTfU8lB/aOPQkAx+mksQcAAABWsL1fTXZ9NJk/mHQnp52bfP9PJqecNfZkACyBM4oAAICl+b9nkq9sTw7tG4qiQ8kLu5Mv3jspjQBYcRRFAADA0uyZS+a/9aLFTg6+kDz/9VFGAuD4KIoAAICl+ebeJPOL7zv4/ExHAWA6FEUAAMDSnPmGZM26l673fPLq9bOfB4DjpigCAACW5pzNyclnJLX2yNqadZN1N7MGWJE89QwAAFiatScnb/z5ZPcjyTNPTrbPuzQ5e/PYkwGwRIoiAABg6U46Ndlw9eQLgBXPpWcAAAAAJFEUAQAAADBQFAEAAACQRFEEAAAAwEBRBAAAAEASRREAAAAAA0URAAAAAEkURQAAAAAMFEUAAAAAJFEUAQAAADBQFAEAAACQRFEEAMft6aefztzcXJ599tmxRwEAgOOiKAKAJTp48GBuueWWbNiwIVdffXXOP//83HrrrZmfnx97NAAAWBJFEQAs0e23357t27dn//79ee6557J///5s27Ytd95559ijAQDAklR3jz3Dt23ZsqXn5ubGHgMAjqq7c8YZZ+SFF154yb7zzjsvu3fvHmEqAAB4qap6tLu3HMuxzigCgCU4dOhQ9u3bt+g+9yoCAGClUhQBwBKsW7cuF1100aL7LrvsshlPAwAA06EoAoAluvvuu3PaaadlzZqMYzg3AAAGeklEQVTJ2+natWtz+umn56677hp5MgAAWBpFEQAs0VVXXZVHHnkkN9xwQzZu3Jibbropc3NzueSSS8YeDQAAluSksQcAgJVs8+bNuf/++8ceAwAApsIZRQAAAAAkURQBAAAAMFAUAQAAAJBEUQQAAADAQFEEAAAAQBJFEQAAAAADRREAAAAASRRFAAAAAAwURQAAAAAkURQBAAAAMFAUAQAAAJBEUQQAAADAQFEEAAAAQBJFEQAAAAADRREAAAAASRRFAAAAAAwURQAAAAAkURQBAAAAMKjuHnuGb6uq/0rytWM49OwkTy/zOHCYvDFL8sYsyRuzJG/MkrwxS/LGLC01b9/X3eccy4GvqKLoWFXVXHdvGXsOTgzyxizJG7Mkb8ySvDFL8sYsyRuzNIu8ufQMAAAAgCSKIgAAAAAGK7Uo+qOxB+CEIm/MkrwxS/LGLMkbsyRvzJK8MUvLnrcVeY8iAAAAAKZvpZ5RBAAAAMCUraiiqKp+q6oer6qdVfXJqjp/WK+q+t2q2jXsv2TsWVn5qur9VfWlIVMfraqzFuy7bcjbl6vqrWPOycpXVW+vqi9U1XxVbXnRPllj6qrqmiFTu6rqvWPPw+pTVR+qqqeq6okFa6+pqoer6qvDn9815oysDlW1oao+XVVPDu+l7xnW5Y2pq6pXVdXnquqxIW+/May/vqo+O+Tt/qo6eexZWT2qam1Vfb6qPj5sL3veVlRRlOT93b2pu9+U5ONJfm1Y/5EkFw5fv5DkD0aaj9Xl4SRv7O5NSb6S5LYkqaqNSd6R5AeTXJPk96tq7WhTsho8keQnknxm4aKssRyGDN2dyXvnxiQ3DlmDafqTTH5uLfTeJJ/q7guTfGrYhuN1KMkvdfdFSS5P8u7hZ5q8sRwOJHlzd29O8qYk11TV5Ul+O8ldQ96eTfJzI87I6vOeJE8u2F72vK2ooqi7n1uweXqSwzdYuj7Jn/bEjiRnVdVrZz4gq0p3f7K7Dw2bO5KsH15fn+TD3X2gu/8tya4kl44xI6tDdz/Z3V9eZJessRwuTbKru/+1u7+Z5MOZZA2mprs/k+S/X7R8fZJ7h9f3JvnxmQ7FqtTdu7v7n4bXz2fyYep1kTeWwfB583+HzXXDVyd5c5K/GNbljampqvVJfizJHw/blRnkbUUVRUlSVe+rqm8keWeOnFH0uiTfWHDYvw9rMC0/m+QTw2t5Y1ZkjeUgV4zle7p7dzL5cJ/k3JHnYZWpqguS/FCSz0beWCbDZUA7kzyVyRUI/5Jk74JfMHtfZZo+kORXkswP29+dGeTtFVcUVdXfVtUTi3xdnyTdfUd3b0hyX5JfPPzXFvlWHufGUR0tb8Mxd2RyWvN9h5cW+Vbyxnd0LFlb7K8tsiZrHC+5Aladqnp1ko8k2fqiqxBgqrr7W8OtUNZncpbuRYsdNtupWI2q6tokT3X3owuXFzl06nk7adrf8Hh191uO8dA/S/LXSX49kxZtw4J965P855RHYxU6Wt6q6uYk1ya5ursP/wOUN162l/GzbSFZYznIFWPZU1Wv7e7dwy0Cnhp7IFaHqlqXSUl0X3f/5bAsbyyr7t5bVX+fyb2xzqqqk4azPLyvMi0/nOS6qvrRJK9KcmYmZxgte95ecWcUfSdVdeGCzeuSfGl4/UCSnx6efnZ5kv85fKopLFVVXZPkV5Nc1937Fux6IMk7quqUqnp9JjdR/9wYM7LqyRrL4R+TXDg8MePkTG6Y/sDIM3FieCDJzcPrm5N8bMRZWCWG+3VsS/Jkd//Ogl3yxtRV1TmHn4RcVacmeUsm98X6dJIbhsPkjano7tu6e313X5DJ/9f+rrvfmRnkrY6cJPHKV1UfSfIDmVyf97Uk7+ru/xjeID6YydM19iX5me6eG29SVoOq2pXklCTPDEs7uvtdw747Mrlv0aFMTnH+xOLfBY6uqt6W5PeSnJNkb5Kd3f3WYZ+sMXXDb6Y+kGRtkg919/tGHolVpqr+PMlVSc5OsieTM8D/Ksn2JN+b5OtJ3t7dL77hNbwsVXVlkn9I8s85cg+P2zO5T5G8MVVVtSmTmwevzeSki+3d/ZtV9YZMHg7xmiSfT/JT3X1gvElZbarqqiS/3N3XziJvK6ooAgAAAGD5rKhLzwAAAABYPooiAAAAAJIoigAAAAAYKIoAAAAASKIoAgAAAGCgKAIAAAAgiaIIAAAAgIGiCAAAAIAkyf8D63sy5/1NUykAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "fig = plt.figure(figsize=(20, 20))\n",
    "\n",
    "plt.subplot(2, 1, 1)\n",
    "F_train = features[train_mask == 1]\n",
    "emb = PCA(n_components=2).fit_transform(F_train)\n",
    "plt.scatter(emb[:, 0], emb[:, 1], c=y_train[train_mask == 1, 0], cmap=plt.cm.copper)\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "F_test = features[test_mask == 1]\n",
    "emb = PCA(n_components=2).fit_transform(F_test)\n",
    "plt.scatter(emb[:, 0], emb[:, 1], c=y_test[test_mask == 1, 0], cmap=plt.cm.copper)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8ec8921cf8>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HSf5u52B3f2Tk4Kpan+TlWbpqNGtdksdmXj8+je1u/PEVxld6z0uSXJIkJ5988sg2AQAA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\nElAAAACDBBQAAMCg/w8f1jwrAfe8/gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8ec85f3438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(features)\n",
    "df[y == 1].mean().mean(), df[y == 1].var().mean()\n",
    "df[y == 0].mean().mean(), df[y == 0].var().mean()\n",
    "df['degree'] = network_np.sum(axis=1)\n",
    "df['label'] = y\n",
    "\n",
    "# get betweenness\n",
    "bet = nx.betweenness_centrality(network)\n",
    "df['betweenness'] = 0\n",
    "for k, v in bet.items():\n",
    "    df.loc[int(k), 'betweenness'] = v\n",
    "\n",
    "# get core number\n",
    "core = nx.core_number(network)\n",
    "df['core'] = 0\n",
    "for k, v in core.items():\n",
    "    df.loc[int(k), 'core'] = v\n",
    "\n",
    "# plot\n",
    "fig = plt.figure(figsize=(14, 8))\n",
    "seaborn.violinplot(x='label', y='core', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
